Network and cloud access controlsAdditional if: Employee AI traffic crosses managed web or cloud controls · Employee AI traffic passes through security controls for web, cloud, or business applications.Employee AI access and usage controlsDirectly addresses · Discover employee AI use and control access to approved and unapproved AI services.AI data protectionDirectly addresses · Inspect prompts, responses, and files to prevent sensitive data from moving through AI tools.Sensitive-data discovery and accessDirectly addresses · Discover sensitive company data that AI can access and identify where that data enters AI-enabled business workflows.Browser and extension controlsAdditional if: Employees use a managed browser or extension · Employees use AI through a managed browser or browser extension where data and session controls can operate.
Vendor research
Netskope AI Security
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.
- $709M annual revenue (2026-01-31)
- 1000+ employees
Company context
Public company (Nasdaq: NTSK)
Netskope reports 4,000+ customers worldwide, 30%+ Fortune 100 customers, and a NewEdge private cloud in more than 80 regions
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 18
- Evaluation requirements
- 19 in this research model
- Unresolved requirements
- 1
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.
Founded2012
HeadquartersSanta Clara, California
OwnershipPublic company (Nasdaq: NTSK)
Employees1000+
Capital and scalePlatform provider
Netskope
- Latest annual company revenue
- $709M
- Operating scale
- Netskope reports 4,000+ customers worldwide, 30%+ Fortune 100 customers, and a NewEdge private cloud in more than 80 regions
- Backing context
- Raised $908M in a 2025 IPO; previously venture and growth backed
Netskope Inc · period ended 2026-01-31 · filed 2026-03-31
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
- 2012
- 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 limits5 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 sourceNetskope One AI Security pageNetskope positions Netskope One AI Security across enterprise apps, private models, agents, shadow AI, GenAI SaaS, AI-powered applications, and autonomous agents.Company sourceNetskope company pageNetskope's company page lists Santa Clara headquarters, NewEdge scale, customer stats, and company scale.Company sourceMarketWatch IPO coverageMarketWatch reported Netskope's 2025 IPO, Nasdaq ticker NTSK, and $908M raised.Company information sourceStored company websiteSupports the company facts shown in this profile.Regulatory filing10-K annual filingNetskope Inc (NTSK) · period ended 2026-01-31
Solution areas
These areas describe how the vendor approaches enterprise AI security. They do not establish product quality or fit.
Buyer context
- For current Netskope SASE/SSE customers, treat Netskope AI Security as an extension path for existing policy, data loss prevention (DLP), cloud access security broker (CASB)/SWG, browser, and traffic-control investments.
- For non-Netskope customers, compare whether adopting a SASE/SSE control plane is justified by AI security requirements versus using a narrower AI security point solution.
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
- 17
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 16
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 16
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 16
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 16
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 16
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 16
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 16
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 16
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 16
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 4
- 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
Strong 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
Strong 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
Strong public supportTest 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
Limited public supportDiscover, 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
Strong 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
Strong 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
Limited public supportAuthorize, 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
Limited public supportInventory, 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
Limited public supportDiscover 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 19 source records. Open additional records only when needed.
Netskope claims unified AI governance using AI inventory, risk assessments, interaction logs, compliance mappings, policy controls, guardrails, and a single platform policy framework.
Log detailed session information, including initializations, tool requests, and responses, to provide the transparency required for AI governance.
Netskope claims automated, scheduled adversarial simulations using more than 18,000 scenarios, multi-turn attacks, continuous risk tracking, and application programming interface (API)-based CI/CD release screening.
Automating adversarial simulations and integrating into CI/CD pipelines to help you uncover vulnerabilities.
Netskope claims an Model Context Protocol (MCP) Catalog and inventory spanning local, containerized, remote, and code-repository Model Context Protocol (MCP) servers with risk assessment and access controls.
An inventory of publicly available MCP servers (remote and code repositories).
Netskope claims an AI Gateway and Agentic Broker with real-time decoding, inspection, data loss prevention (DLP), guardrails, and granular blocking policies for prompts, responses, Model Context Protocol (MCP) servers, tools, and traffic.
Advanced real-time protection policy controls.
Netskope claims policy-based access control for autonomous non-human Model Context Protocol (MCP) interactions and visibility across Model Context Protocol (MCP) clients, servers, tools, resources, and prompt requests.
Scale your autonomous AI, and secure autonomous, non-human interactions, with unified visibility and control of public MCP servers.
Netskope claims real-time protection and data loss prevention (DLP) for Model Context Protocol (MCP) client applications including AI code editors and developer tools, with discovery and blocking of Model Context Protocol (MCP) servers, tools, resources, and requests.
Real-time protection when using MCP client applications including AI code editors, chat interfaces, and developer tools.
Show 13 additional evidence records
Netskope documents AI Gateway as a subscription licensed by gateway instances and monthly transaction allocations, with separate tenant entitlements and add-on packages for more gateways or transactions.
Each Subscription Unit entitles the Customer to one Gateway instance and a fixed allocation of Transactions per calendar month.
Netskope claims Netskope One AI Security provides visibility and controls across enterprise apps, private models, agents, and shadow AI.
Unified AI security for every interaction, from enterprise apps, private models, and agents, to shadow AI.
Netskope claims it can see and secure generative AI software as a service (SaaS), privately hosted large language models (LLMs), AI-powered applications, and autonomous agents.
See and secure your AI ecosystem across generative AI SaaS, privately hosted LLMs, AI-powered applications, and autonomous agents.
Netskope claims generative AI App Security provides visibility across personal, corporate, approved, and shadow generative AI usage.
Gain complete visibility and enforce policies across your entire genAI footprint: personal to corporate, sanctioned to shadow.
Netskope claims it can enforce policies across generative AI use and provide access controls for enterprise AI adoption.
Gain complete visibility and enforce policies across your entire genAI footprint: personal to corporate, sanctioned to shadow.
Netskope claims it inspects and sanitizes AI prompts and responses in real time and protects sensitive data across AI apps.
Inspect and sanitize every prompt and response in real time, with a unified defense against AI threats, misuse, and data loss.
Netskope claims cloud app controls for generative AI include real-time access, out-of-band data protection, and security posture management.
Secure the GenAI era with Netskope's proven cloud app controls, from real-time access and out-of-band data protection to security posture management.
Netskope claims AI Gateway secures AI-powered applications as data risk shifts to autonomous app-to-large language model (LLM) application programming interface (API) calls.
As you build AI-powered applications, data risk shifts from human prompts to autonomous app-to-LLM API calls.
Netskope claims AI Command Center provides visibility across generative AI apps and autonomous agents.
Gain comprehensive visibility across your entire AI environment, from genAI apps to autonomous agents
Netskope claims Agentic Broker secures autonomous non-human interactions and provides visibility and control for public Model Context Protocol (MCP) servers.
Scale your autonomous AI, and secure autonomous, non-human interactions, with unified visibility and control of public MCP servers.
Netskope claims visibility into non-human activity for AI agent interactions through Model Context Protocol (MCP) traffic monitoring.
Monitor the MCP traffic that enables your AI agent interactions, giving visibility into non‑human activity and preventing unauthorized data access or risky connections.
No public Netskope AI Security claim found for operational AI spend attribution, budget controls, rate-limit cost governance, or model-routing cost optimization.
No quoted source text is recorded for this claim.
Netskope positions AI Security inside Netskope One, so current Netskope SASE/SSE customers should evaluate incremental enablement, policy reuse, and license scope before adding a separate AI security control plane.
Here's your chance to experience the Netskope One single-cloud platform first-hand.