Sensitive-data discovery and accessDirectly addresses · Discover sensitive company data that AI can access and identify where that data enters AI-enabled business workflows.AI data protectionDirectly addresses · Inspect prompts, responses, and files to prevent sensitive data from moving through AI tools.
Vendor research
Microsoft Purview DSPM for AI
Review what this vendor says publicly, the security topics those statements may support, what remains unverified, and factual company context. This is not an assessment of product effectiveness or fit.
Use-case context
How this vendor relates to the selected use case
Related research availableBack to use case →
These links show approaches associated with this vendor. The relationship label describes how the approach maps to the use case—not product effectiveness, complete requirement coverage, or fit.
Company scale
Established?
EstablishedA provider with at least $1B in annual revenue, at least 1,000 employees, or backing from an established owner.This is a company-maturity signal, not a product-quality rating.
?
EstablishedA provider with at least $1B in annual revenue, at least 1,000 employees, or backing from an established owner.This is a company-maturity signal, not a product-quality rating.A descriptive band derived from retained public revenue, workforce, ownership, or funding signals.
Company scale is separate from product features, effectiveness, and suitability.
- $281.7B annual revenue (2025-06-30)
- 1000+ employees
- Founded 1975
Company context
Public company (Nasdaq: MSFT)
Microsoft positions Purview controls across Copilot experiences, enterprise AI apps, other detected generative AI apps, browser activity, Microsoft 365 data, endpoints, auditing, and compliance workflows
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 18 records
- Source-checked records
- 12
- Evaluation requirements
- 18 in this research model
- Unresolved requirements
- 6
Company intelligence
Who is behind the product
Company facts provide evaluation context. Each signal is kept separate because tenure, workforce, funding, and hiring answer different questions.
Founded1975
HeadquartersRedmond, Washington
OwnershipPublic company (Nasdaq: MSFT)
Employees1000+
Capital and scalePlatform provider
Microsoft
- Latest annual company revenue
- $281.7B
- Operating scale
- Microsoft positions Purview controls across Copilot experiences, enterprise AI apps, other detected generative AI apps, browser activity, Microsoft 365 data, endpoints, auditing, and compliance workflows
- Backing context
- Public company; Microsoft Purview DSPM for AI is part of the Microsoft Security and compliance portfolio
MICROSOFT CORP · period ended 2025-06-30 · filed 2025-07-30
Founders and leadershipBackground context
Current leadership and public filings provide more useful context for this company than historical founder information.
Operating signalsRead each signal separately
There is no combined company rating. The company-scale label uses stated size thresholds; product features and effectiveness require separate evidence.
- Company tenure
- 1975
- Workforce scale
- 1000+
- Hiring activity
- Not displayed
A current count requires a retained, clickable source URL.
Open research questions
- A current hiring source is not available, so the count is not shown.
Company sources and research limits4 linked public sources
Only company facts supported by retained public sources are shown. Missing values remain unknown, and company scale does not establish product effectiveness.
Company sourceMicrosoft Learn Purview AI protectionsMicrosoft Learn describes Microsoft Purview data security and compliance protections for Copilot, agents, enterprise AI apps, and other generative AI apps.Company sourceMicrosoft about pageMicrosoft's about page states its mission and describes Microsoft products, Microsoft Cloud, Copilot, Microsoft AI, and Microsoft Security context.Company information sourceStored company websiteSupports the company facts shown in this profile.Regulatory filing10-K annual filingMICROSOFT CORP (MSFT) · period ended 2025-06-30
Solution areas
These areas describe how the vendor approaches enterprise AI security. They do not establish product quality or fit.
Buyer context
- For Microsoft 365, Purview, Defender for Cloud Apps, Defender XDR, Entra, or Copilot customers, evaluate Purview data security posture management (DSPM) for AI as a baseline control before adding another AI security point product.
- Particularly relevant when the buyer's main AI risk is proprietary or regulated data exposure through Copilot, ChatGPT Enterprise, Claude Enterprise, Gemini, browser-based generative AI, or Microsoft Foundry-connected apps.
- Do not score Purview as an Model Context Protocol (MCP), agent-to-agent (A2A), or AI agent identity product without additional Microsoft evidence beyond the reviewed Purview data-security materials.
Related frameworks
Where public vendor statements relate to framework requirements
11 related frameworks · expand when needed
Related frameworks
Where public vendor statements relate to framework requirements
These links show related requirements for further review. They do not establish framework compliance or control implementation. Open the full framework crosswalk →
Current referenceCSA AI Controls Matrix
- Requirements with public support
- 12
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 3
- Related requirements
- 3
- References
- 3
Evaluation questions
What to verify beyond public claims
These questions come from security requirements with some public support. Use them as starting points for demonstrations, documentation review, customer references, or a buyer-observed pilot.
- 01Unapproved AI use discovery
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
- 02Unapproved AI use discovery
The test user's AI usage activity can be filtered or exported with AI-specific context.
- 03AI-feature discovery in business applications
A software as a service (SaaS) app with an embedded AI feature appears in the software as a service (SaaS) AI inventory with app, provider, and feature context.
- 04AI-feature discovery in business applications
The inventory shows which users, data classes, integrations, or providers are associated with the AI-enabled software as a service (SaaS) app.
- 05Approved AI usage monitoring
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
- 06Approved AI usage monitoring
Prompt, model, or admin activity can be exported or correlated for the selected approved AI platform.
- 07Controls for unapproved AI use
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
- 08Controls for unapproved AI use
The control event records policy reason, user, destination, action, and timestamp.
Detailed security-requirement research18 evaluation items · supporting evidence and open research are shown separatelyExpand
Security requirementPublic supportRelated frameworksWhat to verify
Unapproved AI use discovery
Strong public supportDiscover and monitor workforce AI tools, accounts, prompts, domains, models, users, and usage outside approved controls.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
AI-feature discovery in business applications
Strong public supportInventory software as a service (SaaS) applications that embed AI features, expose enterprise data to AI capabilities, or create AI-driven data movement.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A software as a service (SaaS) app with an embedded AI feature appears in the software as a service (SaaS) AI inventory with app, provider, and feature context.
Approved AI usage monitoring
Strong public supportMonitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Controls for unapproved AI use
Limited public supportBlock, coach, redirect, or contain non-approved AI use and policy-violating AI interactions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
Sensitive-data protection for generative AI
Strong public supportDetect, classify, redact, or block sensitive data in prompts, responses, files, retrieval, memory, and AI-connected workflows.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
Browser and business-application controls
Strong public supportApply session-level controls in browser and software as a service (SaaS) workflows, including uploads, downloads, copy/paste, sharing, and identity-aware access decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A session-level policy controls upload, download, copy, paste, sharing, or form submission in a browser or software as a service (SaaS) workflow.
Generative AI application security
Limited public supportProtect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
AI governance, risk, and compliance
Limited public supportInventory AI systems and owners, translate policy and regulatory obligations into governed workflows, assess risk, manage approvals and exceptions, and retain audit evidence across the AI lifecycle.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
AI assurance and adversarial testing
No supporting claim foundTest models, applications, retrieval-augmented generation (RAG) systems, and agents before release and continuously thereafter using adversarial probes, evaluation suites, attack simulation, and security release gates.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A controlled test campaign exercises an AI model, application, or agent against named AI attack classes.
AI model and supply-chain security
No supporting claim foundDiscover, inventory, scan, validate, and monitor models, datasets, model artifacts, registries, dependencies, and AI development assets for tampering, unsafe serialization, provenance gaps, or malicious content.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test model or AI artifact appears in inventory with origin, version, hash or provenance, and deployment context.
AI gateway, tool-connection, and runtime controls
Limited public supportMediate model, agent, tool, application programming interface (API), connector, and Model Context Protocol (MCP) traffic through an enforcement point that applies identity-aware policy, content controls, routing, rate limits, and auditable allow or deny decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A model, agent, tool, or Model Context Protocol (MCP) request passes through a named policy enforcement point.
Action-taking agent monitoring
Limited public supportObserve and govern agent plans, memory, tool calls, delegated tasks, autonomy, runtime decisions, and outcomes.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent run captures plan, steps, tool calls, outcome, and timestamps.
Agent-to-agent communication security
No supporting claim foundAuthorize, log, and control agent-to-agent, agent-to-tool, Model Context Protocol (MCP), connector, and tool-chain handoffs.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An agent, tool, connector, or Model Context Protocol (MCP) handoff logs source identity, destination, and authorization decision.
Non-human identity and service-account security
No supporting claim foundInventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
AI agent identity and permissions
Limited public supportRegister AI agents as accountable identities, bind them to owners and delegating users, authorize task- and tool-level access, issue short-lived credentials, review access, and revoke or suspend agent authority.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent is registered with a unique identity, accountable owner, purpose, and permitted resources.
AI coding-agent and workstation security
No supporting claim foundDiscover and govern AI coding agents, integrated development environment (IDE) assistants, command-line agents, skills, hooks, extensions, Model Context Protocol (MCP) tools, filesystem access, commands, network activity, secrets, and software-supply-chain actions on developer workstations and build environments.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test coding agent and its skills, hooks, extensions, or Model Context Protocol (MCP) tools appear in an attributable inventory.
AI cost and usage controls
No supporting claim foundVisibility, attribution, budgeting, rate limiting, anomaly detection, and optimization for AI usage and spend across models, agents, workflows, and owners.
Commercial MetadataNIST AI RMF PlaybookNIST Cybersecurity Framework 2.0ISO/IEC 42001OWASP Agentic AI Security Solutions Landscape
A controlled AI usage event is attributed to user, team, model, workflow, or owner with cost or token metrics.
Licensing model
Strong public supportPublicly discoverable commercial model such as per user, per seat, per app, per token, per integration, or enterprise platform license.
The vendor can map the sourced commercial model to per-user, per-seat, per-app, per-token, per-integration, or platform packaging.
Public sources
Vendor statements and quoted evidence
Showing the first 6 of 18 source records. Open additional records only when needed.
Microsoft claims Purview data security posture management (DSPM) and data security posture management (DSPM) for AI help discover, secure, and apply compliance controls for AI usage across the enterprise.
discover, secure, and apply compliance controls for AI usage across your enterprise.
Microsoft says Purview-supported AI app categories include other AI apps detected through browser activity and categorized as generative AI in the Defender for Cloud Apps catalog.
Other AI apps that are detected through browser activity and categorized as "Generative AI" in the Defender for Cloud Apps catalog.
Microsoft claims supported AI app interactions can be monitored per user in the tenant and prompts and responses can flow into Purview activity views.
Interactions using supported AI apps can be monitored for each user in your tenant.
Microsoft says Endpoint data loss prevention (DLP) policies can warn or block users from sharing sensitive information with third-party generative AI sites accessed through a browser.
warn or block users from sharing sensitive information with third-party generative AI sites that are accessed via a browser.
Microsoft says Purview-supported AI apps use existing controls so tenant data is not returned or used by an large language model (LLM) when the user lacks access.
ensure that data stored in your tenant is never returned to the user or used by a large language model (LLM) if the user doesn't have access to that data.
Microsoft says Purview Endpoint data loss prevention (DLP) can warn or block browser-based sharing of sensitive information with third-party generative AI sites.
Windows computers that are onboarded to Microsoft Purview can be configured for Endpoint data loss prevention (DLP) policies
Show 12 additional evidence records
Microsoft says Purview Insider Risk Management has a risky AI usage policy template for prompt injection and protected-material access signals.
Use the Risky AI usage policy template to detect risky usage that includes prompt injection attacks and accessing protected materials.
Microsoft says supported AI agents inherit the same Purview security and compliance capabilities as their parent AI app.
Where these AI apps support agents, they inherit the same security and compliance capabilities as their parent AI app.
Microsoft Purview AI protection materials reviewed did not provide a clear Model Context Protocol (MCP), agent-to-agent (A2A), or agent-to-agent security control claim.
No quoted source text is recorded for this claim.
Microsoft Purview AI protection materials reviewed did not provide a clear non-human identity or service-account lifecycle security claim.
No quoted source text is recorded for this claim.
Microsoft Purview claims security and compliance oversight for AI-agent interactions, including inventory, data security posture management (DSPM) reporting, audit, retention, eDiscovery, communication compliance, and policy recommendations.
All the listed agents are supported by DSPM for AI and have their own dedicated Apps and agents page.
Microsoft Purview materials reviewed did not provide a public product claim for automated adversarial testing, agent or model red teaming, repeatable attack suites, or release-gate evaluation.
No quoted source text is recorded for this claim.
Microsoft Purview materials reviewed did not provide a public product claim for model artifact scanning, provenance, signing, tamper analysis, dependency inventory, or registry release controls.
No quoted source text is recorded for this claim.
Microsoft Purview claims data loss prevention (DLP), sensitivity-label, risky-interaction, and unethical-behavior policies across prompts and responses for supported AI applications and agents.
This recommendation creates a policy to help calculate user risk by detecting risky prompts and responses.
Microsoft Purview claims dedicated visibility and data-security or compliance coverage for supported agents, including Entra-registered and Foundry agents, while inheriting protections from the parent AI application.
AI agents have the same security and compliance protections for AI interactions as their parent AI app.
Microsoft Purview materials reviewed did not provide a public product claim for governing coding-agent commands, developer-workstation files or networks, integrated development environment (IDE) extensions, skills, hooks, secrets, or package actions.
No quoted source text is recorded for this claim.
Microsoft Purview data security posture management (DSPM) for AI materials reviewed did not establish AI workload cost attribution, token or spend metrics, budgets, chargeback, or cost-aware model routing.
No quoted source text is recorded for this claim.
Microsoft documents data security posture management (DSPM) access through Microsoft 365 E5 or Microsoft Purview Suite, while managing some AI-agent interactions can additionally require pay-as-you-go billing.
To access and use DSPM, you need a Microsoft 365 E5 or Microsoft Purview Suite license.