Microsoft Defender for Cloud Features

Access pre-built and custom reports and dashboards.

Creates new or streamlines existing workflows to better handle IT support tickets and service.

Provides Administration tools/console that are easy to use and learn for routine maintenance tasks

Allows users to create, edit, and relinquish user access privileges.

Provides required reports to manage business. Provides adequate logging to troubleshoot and support auditing.

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc. with other software applications.

Constantly monitors acivity related to user behavior and compares activity to benchmarked patterns.

Stores data securely either on premise or in an adjacent cloud database to prevent loss of data at rest.

Analyzes data associated with security configurations and infrastructure to provide vulnerability insights and best practices.

Analyzes data associated with denied entries and policy enforcement, giving information of better authentication and security protocols.

Provides risk scoring for suspicious activity, vulnerabilities, and other threats.

Provides tools for managing authentication credentials such as keys and passwords.

Analyzes data associated with security configurations and infrastructure to provide vulnerability insights and best practices.

Monitors configuration rule sets and policy enforcement measures and document changes to maintain compliance.

Allows administrators to set policies for security and data governance.

Analyzes data associated with web traffic and site performance to provide vulnerability insights and best practices.

Creates new or streamlines existing workflows to better handle IT support tickets and service.

Streamline the flow of work processes by establishing triggers and alerts that notify and route information to the appropriate people when their action is required within the compensation process.

Integrates additional security tools to automate security and incident response processes.

Allows users to track and control activity across cloud services and providers.

Provides image verification features to establish container approval requirements and continuously monitor for policy violations to identify containers with known vulnerabilities, malware, and other threats.

Constantly monitors acivity related to user behavior and compares activity to benchmarked patterns and fraud indicators.

Generate insights across IT systems utilizing event metrics, logging, traces, and metadata.

Optimizes resource allocation.

Consistently monitors processes for applications and IT infrastructure to detect anomalies in real-time.

Sets up standard performance baseline to compare live container activities.

Traces connections between different containerized environments and detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Scans application and image source code for security flaws without executing it in a live environment

Monitors container activities and detects threats across containers, networks, and cloud service providers.

Protects compute resources across a networks and cloud service providers. Serves as Firewall and prompts additional authentication for suspicious users.

Allows administrative control over network components, mapping, and segmentation.

Monitors data quality and sends alerts based on violations or misuse.

Constantly monitors acivity related to user behavior and compares activity to benchmarked patterns.

Stores data securely either on premise or in an adjacent cloud database to prevent loss of data at rest.

Analyzes data associated with denied entries and policy enforcement, giving information of better authentication and security protocols.

Monitors data quality and send alerts based on violations or misuse.

Identifies potential network security risks, vulnerabilities, and compliance impacts.

Creates reports outlining log activity and relevant metrics.

Does not falsely indicate vulnerable code when no vulnerabilitiy legitimately exists.

Allows users to set custom code standards to meet specific compliances.

Detects vulnerabilities at a rate suitable to maintain security, or allows collaborators to do the same.

Allows users to create, edit, and relinquish user access privileges.

Ensures user access management, data lineage, and data encryption.

Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards.

Supports a useful and wide variety of programming languages.

Integrates seamlessly with the build environment and development tools like repositories, package managers, etc.

Grants comprehensive user-friendly insight into all open source components.

Provides relevant and helpful suggestions for vulnerability remediation upon detection.

Monitors open source components proactively and continuously.

Comprehensively identifies all open source version updates, vulnerabilities, and compliance issues.

Tracks infrastructure resource needs and alerts administrators or automatically scales usage to minimize waste.

Monitors performance and statistics related to memory, caches and connections.

Detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Actively monitors status of work stations either on-premise or remote.

Provides thorough, actionable feedback regarding security vulnerabilities, or allows collaborators to do the same.

Prioritizes detected vulnerabilities by potential risk, or allows collaborators to do the same.

Provides suggestions for remediating vulnerable code, or allows collaborators to do the same.

Offers data loss prevention tools to protect data from leaving the environments it is allowed to.

Monitors configuration rule sets and policy enforcement measures and document changes to maintain compliance.

Allows users to track and control security policies across cloud services and providers.

Provides a risk-based approach to determining trust within the network.

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc. with other software applications.

Provides all-encompassing display and analysis of environments, resources, traffic, and activity across networks.

Detect new assets as they enter a cloud environments and networks to add to asset inventory.

Facilitates the proactive search for emerging threats as they target servers, endpoints, and networks.

Analyzes your existing cloud, network, and IT infrastructure to outline access points that can be easily compromised.

Stores information related to new and common vulnerabilities and how to resolve them once incidents occur.

Allows for vulnerability ranking by customized risk and threat priorities.

Alerts over email, text, phone call, or more to multiple parties.

Provides information related to unnecessary spending and unused resources.

Gives alerts when incidents arise.

Diagnoses and resolves incidents without the need for human interaction.

Efficiently scales resource usage to optimize spend whith increased or decreased resource usage requirements.

Allows users to search logs for troubleshooting and open-ended exploration of data.

Creates reports outlining resource, underutilization, cost trends, and/or functional overlap.

Presents information and analytics in a digestible, intuitive, and visually appealing way.

Allows users to track log trends.

Directly identifies, or increases identification speed for, root causes for container issues.

Provides paths, suggestions, or other general assistance towards issue resolution.

Proactively identifies trends on container systems that could lead to failures or errors.

Scans containers, workloads, and kubernetes clusters for any misconfigurations or vulnerabilities.

Monitor live environments for anomalies, risks and threats to ensure rapid response.

Integrates with CI/CD pipelines to detect security risks early in the development life cycle.

Consolidate all security data across the tech and cloud stacks into one dashboard.

Offers an AI-powered engine to provide remediation guidance to the user based on the type of threat.

Uses context-aware analysis to identify critical and non-critical risks across vulnerabilities.

Help detect anomalies across cloud workloads which could help present a potential breach.

Offers a unified view of all cloud assets across multi-cloud platforms such as AWS, Azure, GCP etc.

Continuously scans cloud environments for any misconfigurations, and provide benchmarks and guided remediation.

Capability to perform complex tasks without constant human input

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Improves performance based on feedback and experience

Capability to perform complex tasks without constant human input

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Offers managed detection and response services.

Provides specific capability to defend AI assets from adversarial attacks (including prompt injection, data poisoning, model inversion or extraction) without requiring retraining of the underlying model.

Enables automatic inspection of model inputs (prompts) and/or outputs (responses) to prevent unsafe, sensitive or manipulated content.

Monitors the integrity of model weights, dependencies or metadata (for example via SBOM/AIBOM) to detect tampering, drift or unauthorised modification.

Verifies the ability to enforce who or what (users, agents, systems) may access a model or LLM asset.

Detects unusual or harmful runtime behaviour of AI models, agents or workflows (such as unexpected output patterns, excessive permissions use, or unknown agents).

Provides a persistent, searchable audit log of AI‑asset inputs, outputs and interactions (including who/what invoked the model, when, and with what data) for forensics and compliance.

Ensures that the AI‑security platform supports scaling of AI‑asset protection (models, agents, multi‑cloud deployments) and applies governance/compliance frameworks as AI usage grows.

Enables integration of the AI‑security solution with traditional security stacks (SIEM, SOAR, cloud security, application security, identity/access management) to unify visibility and response.

Offers visibility into unmanaged or unauthorized AI/agent use (“shadow AI”) across the organisation and enforces control over such usage (e.g., agent creation, LLM‑based services).

Supports codified, machine‑enforceable security policies targeting AI models/agents (for example, blocking certain categories of prompts, enforcing least‑privilege for model use, enforcing “no external data” rules).

Integrate with existing security infrastructure (SIEM, CASB, IAM, DSPM/CSPM/SSPM) to bring AI‑SPM into the wider security ecosystem.

Discover AI applications, agents, chatbots and integrations across SaaS, APIs and other environments.

Support continuous updates to policies and controls as AI‑tool usage evolves and new threats emerge.

Monitor data flows, permissions and resource access associated with AI integrations and tools.

Enforce AI‑specific security policies in real time, such as limiting agent permissions and blocking unauthorized AI activity.

Continuously assess AI integration risks including misconfigurations, policy violations and exposure to external AI services.

Provide dashboards, risk scores and prioritisation for remediation across the AI‑asset estate.

Monitor AI‑generated content for sensitive/regulated information and apply remediation or blocking controls.

Maintain audit logs, governance controls and reporting tied specifically to AI assets, agent behaviours and integrations.