AI application runtime protectionDirectly addresses · Protect custom AI applications, information-retrieval systems, model calls, prompts, and outputs while they run.Action-taking agent safeguardsDirectly addresses · Observe and govern agent plans, memory, tool use, delegated tasks, and actions while the agent runs.Sensitive-data discovery and accessAdditional if: AI retrieves sensitive company data · Sensitive information retrieved from company data stores must be protected as it enters an AI workflow.
Vendor research
Wiz AI-SPM / Google Cloud
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.
- $402.8B annual revenue (2025-12-31)
- $1.4B known funding
- 250-1000 employees
Company context
Google Cloud product brand; Google completed the Wiz acquisition on March 11, 2026 and retained the Wiz brand
Wiz says it is trusted by more than 50% of Fortune 100 companies and protects 5 million cloud workloads
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 13
- Evaluation requirements
- 19 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.
FoundedFounding year not stated on reviewed Wiz- or Google-controlled pages
HeadquartersHeadquarters not stated on reviewed Wiz-controlled pages
OwnershipGoogle Cloud product brand; Google completed the Wiz acquisition on March 11, 2026 and retained the Wiz brand
Employees250-1000
Capital and scaleIndependent company
Wiz
- Known funding
- $1.4B
- Current owner annual revenue
- $402.8B
- Operating scale
- Wiz says it is trusted by more than 50% of Fortune 100 companies and protects 5 million cloud workloads
- Backing context
- Google Cloud ownership following completed acquisition; historical venture backing not restated from reviewed Wiz-controlled pages
SERIES_C_PLUS · $1B · 2024-05-01
Alphabet Inc. (GOOGL) · period ended 2025-12-31 · filed 2026-02-05
Founders and leadership1 person listed
- Assaf RappaportCurrent role listed
CEO
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
- Founding year not stated on reviewed Wiz- or Google-controlled pages
- Workforce scale
- 250-1000
- 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 sourceWiz homepageWiz says it continuously discovers AI models, agents, MCP servers, and services across cloud and SaaS.Company sourceGoogle Cloud completion announcementGoogle Cloud announced it completed the Wiz acquisition and retained the Wiz brand.Company sourceWiz about pageWiz says more than 50% of Fortune 100 companies are customers and 5 million cloud workloads are protected.Regulatory filing10-K annual filingAlphabet Inc. (GOOGL) · period ended 2025-12-31
Solution areas
These areas describe how the vendor approaches enterprise AI security. They do not establish product quality or fit.
Buyer context
- Treat Wiz AI-SPM as a cloud/CNAPP and AI security-posture platform extension, especially for buyers already operating Wiz Cloud, Wiz Code, or Wiz Defend.
- Public evidence supports cloud and software as a service (SaaS) AI model/agent/Model Context Protocol (MCP) discovery, AI-specific risk posture, sensitive-data exposure risk, runtime response for AI threats, cloud identity context, and modular licensing.
- Public pages reviewed did not expose employee shadow-AI usage discovery, browser/software as a service (SaaS)-session controls, unapproved AI app blocking, or operational AI FinOps controls.
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
- 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.
- 01Approved AI usage monitoring
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
- 02Approved AI usage monitoring
Prompt, model, or admin activity can be exported or correlated for the selected approved AI platform.
- 03Sensitive-data protection for generative AI
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
- 04Sensitive-data protection for generative AI
A policy redacts, blocks, coaches, or records the sensitive data event before it leaves the approved path.
- 05Generative AI application security
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
- 06Generative AI application security
A prompt-injection or unsafe-output test is detected, blocked, or flagged by the guardrail or large language model (LLM) firewall.
- 07AI governance, risk, and compliance
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
- 08AI governance, risk, and compliance
A policy, assessment, approval, exception, or remediation workflow changes the governed state of the test system.
Detailed security-requirement research18 evaluation items · supporting evidence and open research are shown separatelyExpand
Security requirementPublic supportRelated frameworksWhat to verify
Unapproved AI use discovery
No supporting claim foundDiscover 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
No supporting claim foundInventory 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
Limited 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
No supporting claim foundBlock, 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
No supporting claim foundApply 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
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
Strong 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
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
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.
Wiz claims centralized AI inventory, posture, ownership context, compliance mapping, security baselines, prioritized risk, and remediation workflows across models, agents, services, data, infrastructure, and applications.
AI-SPM is designed to secure AI pipelines and accelerate AI adoption while maintaining protection against AI-related risks.
Wiz AI-SPM materials reviewed did not provide a public product claim for automated adversarial testing, model or agent red teaming, repeatable attack suites, or release-gate evaluation.
No quoted source text is recorded for this claim.
Wiz claims an AI bill of materials covering models, frameworks, dependencies, and libraries, plus model artifact scanning, repository and pipeline visibility, and attack-path analysis for model and training-data risk.
Analyze the components powering AI systems including models, frameworks, dependencies, and libraries.
Wiz claims runtime detection and response for prompt injection, rogue agents, malicious AI behavior, and Model Context Protocol (MCP)-connected AI systems using sensor and cloud telemetry.
Stop AI-native threats including prompt injection, rogue agents, and malicious AI behavior at runtime.
Wiz claims agent inventory and contextual mapping of agents to identities, workloads, data, access, capabilities, owners, and blast radius, with CIEM and secure-baseline checks.
Contextual Correlation: maps agents to the identities, workloads, and data they touch.
Wiz claims coding-agent and AI-integrated development environment (IDE) integrations that bring cloud and AI context into development, generate code fixes, and prevent cloud and AI risks from reaching production.
Meet your developers where they are and how they work with coding agent integrations that fix cloud and AI risks at the source.
Show 13 additional evidence records
Wiz materials reviewed did not provide a public claim for employee AI app discovery, unapproved employee AI usage, prompt/user activity inventory, or AI domain detection.
No quoted source text is recorded for this claim.
Wiz materials reviewed did not provide a public claim for embedded software as a service (SaaS) AI feature inventory or employee third-party software as a service (SaaS) AI monitoring.
No quoted source text is recorded for this claim.
Wiz claims it continuously discovers AI models, agents, Model Context Protocol (MCP) servers, and services across cloud and software as a service (SaaS).
Continuously discover AI models, agents, MCP servers, and services across cloud and SaaS.
Wiz materials reviewed did not provide a public claim for employee unapproved AI app blocking, coaching, allowlists, browser control, or network control.
No quoted source text is recorded for this claim.
Wiz claims AI-specific risk detection covers sensitive data exposure, guardrails, and exposed endpoints.
Identify AI-specific risks — from sensitive data exposure and guardrails to exposed endpoints.
Wiz materials reviewed did not provide a public claim for browser extension enforcement, enterprise browser controls, software as a service (SaaS)-session controls, or identity-aware user software as a service (SaaS) policy.
No quoted source text is recorded for this claim.
Wiz claims it detects and responds to AI runtime threats from data exposure to malicious agent actions.
Detect and respond to AI runtime threats, from data exposure to malicious agent actions.
Wiz claims continuous discovery of AI models, agents, Model Context Protocol (MCP) servers, and services across cloud and software as a service (SaaS).
Continuously discover AI models, agents, MCP servers, and services across cloud and SaaS.
Wiz claims discovery of Model Context Protocol (MCP) servers across cloud and software as a service (SaaS) as part of AI model, agent, and service visibility.
Continuously discover AI models, agents, MCP servers, and services across cloud and SaaS.
Wiz claims real AI risk context connects infrastructure, identity, data, and AI.
Understand real AI risk by connecting context across infrastructure, identity, data, and AI.
Wiz materials reviewed did not provide a public claim for AI spend attribution, model cost routing, budget enforcement, rate limits, runaway token controls, or AI return on investment (ROI) reporting.
No quoted source text is recorded for this claim.
Wiz says its platform licensing is modular and scales with workloads, active developers, log ingestion, or sensors.
Licensing is modular- scaling with your workloads, active developers, log ingestion, or sensors to provide complete security in one platform.
Wiz claims most frontier AI labs rely on Wiz to secure their cloud, AI workloads, and the data powering next-generation innovation.
Most frontier AI labs rely on Wiz to secure their cloud, AI workloads, and the data powering next-generation innovation.