Protecting Your Azure Key Vault: Why Azure RBAC Is Critical for Security
Introduction In today’s cloud-centric landscape, misconfigured access controls remain one of the most critical weaknesses in the cyber kill chain. When access policies are overly permissive, they create opportunities for adversaries to gain unauthorized access to sensitive secrets, keys, and certificates. These credentials can be leveraged for lateral movement, privilege escalation, and establishing persistent footholds across cloud environments. A compromised Azure Key Vault doesn’t just expose isolated assets it can act as a pivot point to breach broader Azure resources, potentially leading to widespread security incidents, data exfiltration, and regulatory compliance failures. Without granular permissioning and centralized access governance, organizations face elevated risks of supply chain compromise, ransomware propagation, and significant operational disruption. The Role of Azure Key Vault in Security Azure Key Vault plays a crucial role in securely storing and managing sensitive information, making it a prime target for attackers. Effective access control is essential to prevent unauthorized access, maintain compliance, and ensure operational efficiency. Historically, Azure Key Vault used Access Policies for managing permissions. However, Azure Role-Based Access Control (RBAC) has emerged as the recommended and more secure approach. RBAC provides granular permissions, centralized management, and improved security, significantly reducing risks associated with misconfigurations and privilege misuse. In this blog, we’ll highlight the security risks of a misconfigured key vault, explain why RBAC is superior to legacy Access Policies and provide RBAC best practices, and how to migrate from access policies to RBAC. Security Risks of Misconfigured Azure Key Vault Access Overexposed Key Vaults create significant security vulnerabilities, including: Unauthorized access to API tokens, database credentials, and encryption keys. Compromise of dependent Azure services such as Virtual Machines, App Services, Storage Accounts, and Azure SQL databases. Privilege escalation via managed identity tokens, enabling further attacks within your environment. Indirect permission inheritance through Azure AD (AAD) group memberships, making it harder to track and control access. Nested AAD group access, which increases the risk of unintended privilege propagation and complicates auditing and governance. Consider this real-world example of the risks posed by overly permissive access policies: A global fintech company suffered a severe breach due to an overly permissive Key Vault configuration, including public network access and excessive permissions via legacy access policies. Attackers accessed sensitive Azure SQL databases, achieved lateral movement across resources, and escalated privileges using embedded tokens. The critical lesson: protect Key Vaults using strict RBAC permissions, network restrictions, and continuous security monitoring. Why Azure RBAC is Superior to Legacy Access Policies Azure RBAC enables centralized, scalable, and auditable access management. It integrates with Microsoft Entra, supports hierarchical role assignments, and works seamlessly with advanced security controls like Conditional Access and Defender for Cloud. Access Policies, on the other hand, were designed for simpler, resource-specific use cases and lack the flexibility and control required for modern cloud environments. For a deeper comparison, see Azure RBAC vs. access policies. Best Practices for Implementing Azure RBAC with Azure Key Vault To effectively secure your Key Vault, follow these RBAC best practices: Use Managed Identities: Eliminate secrets by authenticating applications through Microsoft Entra. Enforce Least Privilege: Precisely control permissions, granting each user or application only minimal required access. Centralize and Scale Role Management: Assign roles at subscription or resource group levels to reduce complexity and improve manageability. Leverage Privileged Identity Management (PIM): Implement just-in-time, temporary access for high-privilege roles. Regularly Audit Permissions: Periodically review and prune RBAC role assignments. Detailed Microsoft Entra logging enhances auditability and simplifies compliance reporting. Integrate Security Controls: Strengthen RBAC by integrating with Microsoft Entra Conditional Access, Defender for Cloud, and Azure Policy. For more on the Azure RBAC features specific to AKV, see the Azure Key Vault RBAC Guide. For a comprehensive security checklist, see Secure your Azure Key Vault. Migrating from Access Policies to RBAC To transition your Key Vault from legacy access policies to RBAC, follow these steps: Prepare: Confirm you have the necessary administrative permissions and gather an inventory of applications and users accessing the vault. Conduct inventory: Document all current access policies, including the specific permissions granted to each identity. Assign RBAC Roles: Map each identity to an appropriate RBAC role (e.g., Reader, Contributor, Administrator) based on the principle of least privilege. Enable RBAC: Switch the Key Vault to the RBAC authorization model. Validate: Test all application and user access paths to ensure nothing is inadvertently broken. Monitor: Implement monitoring and alerting to detect and respond to access issues or misconfigurations. For detailed, step-by-step instructions—including examples in CLI and PowerShell—see Migrate from access policies to RBAC. Conclusion Now is the time to modernize access control strategies. Adopting Role-Based Access Control (RBAC) not only eliminates configuration drift and overly broad permissions but also enhances operational efficiency and strengthens your defense against evolving threat landscapes. Transitioning to RBAC is a proactive step toward building a resilient and future-ready security framework for your Azure environment. Overexposed Azure Key Vaults aren’t just isolated risks — they act as breach multipliers. Treat them as Tier-0 assets, on par with domain controllers and enterprise credential stores. Protecting them requires the same level of rigor and strategic prioritization. By enforcing network segmentation, applying least-privilege access through RBAC, and integrating continuous monitoring, organizations can dramatically reduce the blast radius of a potential compromise and ensure stronger containment in the face of advanced threats. Want to learn more? Explore Microsoft's RBAC Documentation for additional details.
Introducing the new File Integrity Monitoring with Defender for Endpoint integration
As the final and most complex piece of this puzzle is the release of File Integrity Monitoring (FIM) powered by Defender for Endpoint, marks a significant milestone in the Defender for Servers simplification journey. The new FIM solution based on Defender for Endpoint offers real-time monitoring on critical file paths and system files, ensuring that any changes indicating a potential attack are detected immediately. In addition, FIM offers built-in support for relevant security regulatory compliance standards, such as PCI-DSS, CIS, NIST, and others, allowing you to maintain compliance.Agentless code scanning for GitHub and Azure DevOps (preview)
🚀 Start free preview ▶️ Watch a video on agentless code scanning Most security teams want to shift left. But for many developers, "shift left" sounds like "shift pain". Coordination. YAML edits with extra pipeline steps. Build slowdowns. More friction while they're trying to go fast. 🪛 Pipeline friction YAML edits with extra steps ⏱️ Build slowdowns More friction, less speed 🧩 Complex coordination Too many moving parts That's the tension we wanted to solve. With agentless code scanning in Defender for Cloud, you get broad visibility into code and infrastructure risks across GitHub and Azure DevOps - without touching your CI/CD pipelines or installing anything. ✨ Just connect your environment. We handle the rest. Already in preview, here's what's new Agentless code scanning was released in November 2024, and we're expanding the preview with capabilities to make it more actionable, customizable, and scalable: ✅ GitHub & Azure DevOps Connect your GitHub org and scan every repository automatically 🎯 Scoping controls Choose exactly which orgs, projects, and repos to scan 🔍 Scanner selection Enable code scanning, IaC scanning, or both 🧰 UI and REST API Manage at scale, programmatically or in-portal or Cloud portal 🎁 Available for free during the preview under Defender CSPM How agentless code scanning works Agentless code scanning runs entirely outside your pipelines. Once a connector has been created, Defender for Cloud automatically discovers your repositories, pulls the latest code, scans for security issues, and publishes findings as security recommendations - every day. Here's the flow: 1 Discover Repositories in GitHub or Azure DevOps are discovered using a built-in connector. 2 Retrieve The latest commit from the default branch is pulled immediately, then re-scanned daily. 3 Analyze Built-in scanners run in our environment: Code Scanning – looks for insecure patterns, bad crypto, and unsafe functions (e.g., `pickle.loads`, `eval()`) using Bandit and ESLint. Infrastructure as Code (IaC) – detects misconfigurations in Terraform, Bicep, ARM templates, CloudFormation, Kubernetes manifests, Dockerfiles, and more using Checkov and Template Analyzer. 4 Publish Findings appear as Security recommendations in Defender for Cloud, with full context: file path, line number, rule ID, and guidance to fix. Get started in under a minute 1 In Defender for Cloud, go to Environment settings → DevOps Security 2 Add a connector: Azure DevOps – requires Azure Security Admin and ADO Project Collection Admin GitHub – requires Azure Security Admin and GitHub Org Owner to install the Microsoft Security DevOps app 3 Choose your scanning scope and scanners 4 Click Save – and we'll run the first scan immediately s than a minute No pipeline configuration. No agent installed. No developer effort. Do I still need in-pipeline scanning? Short answer: yes - if you want depth and speed in the development workflow. Agentless scanning gives you fast, wide coverage. But Defender for Cloud also supports in-pipeline scanning using Microsoft Security DevOps (MSDO) command line application for Azure DevOps or GitHub Action. Each method has its own strengths. Here's how to think about when to use which - and why many teams choose both: When to use... ☁️ Agentless Scanning 🏗️ In-Pipeline Scanning Visibility Quickly assess all repos at org-level Scans and enforce every PR and commit Setup Requires only a connector Requires pipeline (YAML) edits Dev experience No impact on build time Inline feedback inside PRs and builds Granularity Repo-level control with code and IaC scanners Fine-tuned control per tool or branch Depth Default branch scans, no build context Full build artifact, container, and dependency scanning 💡 Best practice: start broad with agentless. Go deeper with in-pipeline scans where "break the build" makes sense. Already using GitHub Advanced Security (GHAS)? GitHub Advanced Security (GHAS) includes built-in scanning for secrets, CodeQL, and open-source dependencies - directly in GitHub and Azure DevOps. You don't need to choose. Defender for Cloud complements GHAS by: Surfaces GHAS findings inside Defender for Cloud's Security recommendations Adds broader context across code, infrastructure, and identity Requires no extra setup - findings flow in through the connector You get centralized visibility, even if your teams are split across tools. One console. Full picture. Core scenarios you can tackle today 🛡️ Catch IaC misconfigurations early Scan for critical misconfigurations in Terraform, ARM, Bicep, Dockerfiles, and Kubernetes manifests. Flag issues like public storage access or open network rules before they're deployed. 🎯 Bring code risk into context All findings appear in the same portal you use for VM and container security. No more jumping between tools - triage issues by risk, drill into the affected repository and file, and route them to the right owner. 🔍 Focus on what matters Customize which scanners run and where. Continuously scan production repositories. Skip forks. Run scoped PoCs. Keep pace as repositories grow - new ones are auto-discovered. What you'll see - and where All detected security issues show up as security recommendations in the recommendations and DevOps Security blades in Defender for Cloud. Every recommendation includes: ✅ Affected repository, branch, file path, and line number 🛠️ The scanner that found it 💡 Clear guidance to fix What's next We're not stopping here. These are already in development: 🔐 Secret scanning Identify leaked credentials alongside code and IaC findings 📦 Dependency scanning Open-source dependency scanning (SCA) 🌿 Multi-branch support Scan protected and non-default branches Follow updates in our Tech Community and release notes. Try it now - and help us shape what comes next Connect GitHub or Azure DevOps to Defender for Cloud (free during preview) and enable agentless code scanning View your discovered DevOps resources in the Inventory or DevOps Security blades Enable scanning and review recommendations Microsoft Defender for Cloud → Recommendations Shift left without slowing down. Start scanning smarter with agentless code scanning today. Helpful resources to learn more Learn more in the Defender for Cloud in the Field episode on agentless code scanning Overview of Microsoft Defender for Cloud DevOps security Agentless code scanning - configuration, capabilities, and limitations Set up in-pipeline scanning in: Azure DevOps GitHub action Other CI/CD pipeline tools (Jenkins, BitBucket Pipelines, Google Cloud Build, Bamboo, CircleCI, and more)AZ-500: Microsoft Azure Security Technologies Study Guide
The AZ-500 certification provides professionals with the skills and knowledge needed to secure Azure infrastructure, services, and data. The exam covers identity and access management, data protection, platform security, and governance in Azure. Learners can prepare for the exam with Microsoft's self-paced curriculum, instructor-led course, and documentation. The certification measures the learner’s knowledge of managing, monitoring, and implementing security for resources in Azure, multi-cloud, and hybrid environments. Azure Firewall, Key Vault, and Azure Active Directory are some of the topics covered in the exam.New and enhanced multicloud regulatory compliance standards in Defender for Cloud
Security compliance across multicloud environments is challenging due to the diversity and complexity of platforms. Each cloud provider—whether AWS, Azure, Google Cloud, or others—has its own security protocols, configurations, and compliance requirements. This variation can lead to discrepancies and gaps in security posture, as what works in one cloud environment may not be applied seamlessly in another. Managing multiple compliance frameworks simultaneously adds complexity, especially when each provider has different methods for meeting these standards. Without unified compliance visibility, security teams are forced to monitor each cloud platform independently, which is time-consuming and prone to human error. This fragmentation can lead to missed compliance requirements, especially when resources are limited or when team members are unfamiliar with specific cloud platforms. As a result, organizations face increased risks of data breaches, fines, and reputational damage if they fail to meet regulatory requirements consistently across all platforms. A streamlined approach ultimately strengthens the organization’s security posture and simplifies the path to achieving and maintaining compliance across complex, multi-cloud landscapes. Microsoft Defender for Cloud aids security teams in meeting various regulations and industry standards through our Regulatory Compliance dashboard. Each standard has multiple compliance controls, which are groups of related security recommendations. Defender for Cloud constantly evaluates the environment against these controls, indicating whether resources are compliant or non-compliant. To help security teams streamline with compliance teams, Defender for Cloud regulatory compliance signals can be integrated into Microsoft Purview Compliance Manager. Today, we’re excited to share enhanced and expanded support of over 30 regulatory compliance frameworks in Defender for Cloud, across Azure, AWS, and GCP. New regulatory compliance frameworks for multicloud environments now available in public preview Unified compliance posture assessments actualized to the latest versions with parity across Azure, AWS, and GCP. New regulatory compliance standards include: E.U. Network and Information Security Directive 2 (NIS2) CIS GCP Foundations v3.0 U.S. Criminal Justice Information Services (CJIS) Security Policy, Version 5.9.5 U.S. Federal Financial Institutions Examination Council Cybersecurity Assessment Tool (FFIEC CAT) U.K. National Cyber Security Centre (NCSC) Cyber Essentials v3.1 U.K. National Cyber Security Centre (NCSC) Cyber Assurance Framework (CAF) v3.2 Enhancements to existing regulatory compliance standards Leverage the latest versions of currently supported regulatory compliance standards with expansion to full parity across Azure, AWS, and GCP. Some key standards include: SWIFT Customer Security Controls Framework (2024) E.U. General Data Protection Regulation (GDPR) ISO IEC 27002:2022 NIST CSF v2.0 PCI DSS v4.0.1 NIST SP 800 53 R5.1.1 View the full list of regulatory compliance standards. Get started with regulatory compliance assessment in Defender for Cloud today.
Protecting Azure AI Workloads using Threat Protection for AI in Defender for Cloud
Understanding Jailbreak attacks Evasion attacks involve subtly modifying inputs (images, audio files, documents, etc.) to mislead models at inference time, making them a stealthy and effective means of bypassing inherent security controls in the AI Service. Jailbreak can be considered a type of evasion attack. The attack involves crafting inputs that cause the AI model to bypass its safety mechanisms and produce unintended or harmful outputs. Attackers can use techniques like crescendo to bypass security filters for example creating a recipe for Molotov Cocktail. Due to the nature of working with human language, generative capabilities, and the data used in training the models, AI models are non-deterministic, i.e., the same input will not always produce the same outputs. A “classic” jailbreak happens when an authorized operator of the system crafts jailbreak inputs in order to extend their own powers over the system. Indirect prompt injection happens when a system processes data controlled by a third party (e.g., analyzing incoming emails or documents editable by someone other than the operator) who inserts a malicious payload into that data, which then leads to a jailbreak of the system. There are various types of jailbreak-like attacks. Some, like DAN, involve adding instructions to a single user input, while others, like Crescendo, operate over multiple turns, gradually steering the conversation towards a specific outcome. Therefore, jailbreaks should be seen not as a single technique but as a collection of methods where a guardrail can be circumvented by a carefully crafted input. Understanding Native protections against Jailbreak Defender for Cloud’s AI Threat Protection (https://learn.microsoft.com/en-us/azure/defender-for-cloud/ai-threat-protection) feature integrates with Azure Open AI and reviews the prompt and response for suspicious behavior (https://learn.microsoft.com/en-us/azure/defender-for-cloud/alerts-ai-workloads) In case of Jailbreak, the solution integrates with Azure Open AI’s Content Filter Prompt Shields (https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/content-filter), which uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories. When Prompt Shield detects a Jailbreak attempt, it filters / annotate the user’s prompt. Defender for Cloud then picks up this information and makes it available to the security teams. Note that User Prompts are protected from Direct Attacks like Jailbreak by default. As a result, once you enable Threat Protection for AI in Defender for Cloud your security teams will have complete visibility on these. Fig 1. Threat Protection for AI alert Tangible benefits for your Security Teams Since the Defender for Cloud is doing the undifferentiated heavy lifting here your Security Governance, Architecture, and Operations all benefit like so, Governance Content is available out of the box and is enabled by default in several critical risk scenarios. This helps meet your AI security controls like OWASP LLM 01: Prompt Injection (https://genai.owasp.org/llmrisk/llm01-prompt-injection/) You can further refine the Content Filter levels for each model running in AI Foundry depending on the risk such as the data model accesses (RAG), public exposure, etc. The application of the control is enabled by default The Control reporting is available out of the box and can/will follow the existing workflow that you have set up for remainder of your cloud workloads Defender for Cloud provides Governance Framework Architecture Threat Protection for AI can be enabled at subscription level so the service scales with your workloads and provides coverage for any new deployments There is native integration with Azure Open AI so you do not need to write and manage custom patterns unlike a third party service The service is not in-line so you do not have to worry about downstream impact on the workload Since Threat Protection for AI is a capability within Defender for Cloud, you do not need to define specific RBAC permissions for users or service The alerts from the capability will automatically follow the export flow you have set up for the rest of the Defender for Cloud capabilities. Operations The alerts are already ingested in the Microsoft XDR portal so you can continue threat hunting without learning new tools there by maximizing your existing skills You can set up Workflow Automation to respond to AI alerts much like alerts from other capabilities like Defender for Storage. So, your overall logic app patterns can be reused with small tweaks Since your SOC analyst might still be learning Gen AI threats and your playbooks might not be up to date, the alerts (see Fig 1 above) contain steps that they should take to resolve The alerts are available in XDR portal, which you might already be familiar with so won’t have to learn a new solution Fig 2. Alerts in XDR Portal The alerts contain the prompt as an evidence in addition to other relevant attributes like IP, user details, targeted resource. This helps you quickly triage the alerts Fig 3. Prompt Evidence captured as part of the alert You can train the model using the detected prompts to block any future responses on similar user prompts Summary Threat Protection for AI: Provides holistic coverage of your Gen AI workloads Helps you maximize the investment in Microsoft Solutions Reduces the need for learning another solution to protect another new workloads Drives overall cost, time, and operational efficiencies Enroll in the preview https://learn.microsoft.com/en-us/azure/defender-for-cloud/ai-onboarding#enroll-in-the-limited-preview
Defender for Cloud unified Vulnerability Assessment powered by Defender Vulnerability Management
We are thrilled to announce that Defender for Cloud is unifying our vulnerability assessment engine to Microsoft Defender Vulnerability Management (MDVM) across servers and containers. Security admins will benefit from Microsoft’s unmatched threat intelligence, breach likelihood predictions and business contexts to identify, assess, prioritize, and remediate vulnerabilities - making it an ideal tool for managing an expanded attack surface and reducing overall cloud risk posture.Leveraging Azure native tooling to hunt Kubernetes security issues
This series shows you how you can maximize your investments in Microsoft Security tools by leveraging XDR Portal and Defender for Kubernetes to hunt for security issues. If you are in red team this article will shorten your learning curve by allowing you to identify security issues using KQL with Container Security Alerts. This series is part of “Security using Azure Native services” series and assumes that you are following the series “A guide to using Microsoft Sentinel for monitoring the security of your containerized applications and orchestration platforms” https://techcommunity.microsoft.com/t5/microsoft-sentinel-blog/setting-up-sentinel-for-kubernetes-monitoring/ba-p/4118593
Update OpenSSL : Machines should have vulnerability findings resolved
Hi, I am new to this Defender Cloud. We are getting this message about out of date OpenSSL version: I have updated the .NetCore to the latest version : However it still doesnt seems to have resolved the error from Defender Cloud. I dont have any OpenSSL client installed on this machine from .net core. when I searched I only found these files : any assistance will be greatly appreciated on how do I resolve this issue? as far as I can see everything is up to date.
