AI asset and configuration securityDirectly addresses · Discover approved, unmanaged, and action-taking AI systems along with model and software artifacts that require governance.Agent identity and permissionsAdditional if: Governed agents have delegated authority · The governed environment includes action-taking agents with delegated authority.Machine and workload identityAdditional if: Governed AI uses machine credentials · Governed AI systems use service accounts, API keys, machine identities, or other machine credentials.
Vendor research
Cloudflare AI Security Suite
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.
- $2.2B annual revenue (2025-12-31)
- 1000+ employees
- Founded 2009
Company context
Public company (NYSE: NET)
Cloudflare states that its infrastructure powers approximately 20% of the Internet and spans more than 300 cities
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 17
- Evaluation requirements
- 19 in this research model
- Unresolved requirements
- 2
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.
Founded2009
HeadquartersSan Francisco, California
OwnershipPublic company (NYSE: NET)
Employees1000+
Capital and scalePlatform provider
Cloudflare
- Latest annual company revenue
- $2.2B
- Operating scale
- Cloudflare states that its infrastructure powers approximately 20% of the Internet and spans more than 300 cities
- Backing context
- Public-company investment across Cloudflare One, application security, developer platform, AI Gateway, and global network services
Cloudflare, Inc. · period ended 2025-12-31 · filed 2026-02-26
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
- 2009
- 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 sourceCloudflare AI Security Suite pageCloudflare describes workforce, public application, agentic access, developer, data, identity, gateway, and MCP security controls.Company sourceCloudflare AI Gateway pageCloudflare describes AI Gateway routing, caching, observability, rate limiting, cost and billing controls, logs, and safety guardrails.Company information sourceStored company websiteSupports the company facts shown in this profile.Regulatory filing10-K annual filingCloudflare, Inc. (NET) · 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.
Network and cloud access controlsCore product focusAI application runtime protectionCore product focusAI gateway and tool-connection controlsCore product focusEmployee AI access and usage controlsCore product focusAI API and web application protectionRelated coverageAI data protectionRelated coverageBrowser and extension controlsRelated coverageAI asset and configuration securityRelated coverageAction-taking agent safeguardsRelated coverageAgent identity and permissionsRelated coverageMachine and workload identityRelated coverageAI usage and cost controlsRelated coverage
Buyer context
- Treat Cloudflare AI Security Suite as multiple integrated control planes: workforce SASE, public AI application protection, AI Gateway, Model Context Protocol (MCP) access, developer services, data loss prevention (DLP), and identity-aware access.
- Public evidence supports shadow AI, prompt data loss prevention (DLP), app isolation and blocking, large language model (LLM) endpoint discovery, prompt-injection defenses, model routing, Model Context Protocol (MCP) request logging and least privilege, secret storage and rotation, and AI cost controls.
- Entitlement must be confirmed by component because workforce, application, gateway, Model Context Protocol (MCP), and developer capabilities span different Cloudflare services.
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
- 16
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 15
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 15
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 15
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 15
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 15
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 15
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 15
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 14
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 14
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 5
- 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
Limited 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
Limited 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
Strong 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
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
Strong 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
Strong 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
Strong public supportVisibility, 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.
Cloudflare claims discovery of shadow AI tools across the organization using its SASE platform.
Discover all shadow AI tools across your organization
Cloudflare claims cloud access security broker (CASB) scanning of approved generative AI applications for posture and security risks.
scan sanctioned GenAI apps for security posture risks
Cloudflare claims discovery of AI models and application programming interfaces (APIs) across web properties plus centralized model management in AI Gateway.
Automatically discover all AI models and APIs across your web properties.
Cloudflare claims identity-based rules that block, isolate, redirect, or allow user connections to AI applications.
Block, isolate, redirect, or allow user connections
Cloudflare claims data loss prevention (DLP) and prompt protection that block sensitive data in prompts, responses, and Model Context Protocol (MCP) traffic.
Scan user prompts and model responses to block sensitive data
Cloudflare claims per-app Zero Trust connection policy and prompt-content data loss prevention (DLP) for workforce AI use.
identity-based zero trust rules per app
Show 13 additional evidence records
Cloudflare claims real-time protection for public AI applications against prompt injection, data leaks, harmful content, and PII.
Protect your AI apps and APIs from prompt injection and data leaks in real-time.
Cloudflare claims AI-SPM, policy decisions based on app confidence, audit logs, and controls supporting compliant AI services.
AI security posture management (AI-SPM)
Cloudflare materials reviewed did not provide a public claim for adversarial AI red teaming, evaluation campaigns, or regression release gates.
No quoted source text is recorded for this claim.
Cloudflare claims its AI firewall blocks model poisoning and discovers model and application programming interface (API) endpoints across web properties.
model poisoning
Cloudflare claims AI Gateway and Model Context Protocol (MCP) portals that proxy requests, apply data loss prevention (DLP) and HTTP policy, authenticate connections, and scope tools and permissions.
portal proxies the request to the upstream MCP server
Cloudflare claims aggregated Model Context Protocol (MCP) request logs and AI Gateway request logs with prompts, responses, provider, tokens, cost, duration, and status.
Aggregate all MCP request logs
Cloudflare claims Zero Trust controls for machine-to-machine AI interactions and identity-scoped agent connections to Model Context Protocol (MCP) resources.
machine-to-machine communication
Cloudflare claims secure edge storage of application programming interface (API) keys and secrets with simplified rotation across model providers.
simplifying key rotation across providers
Cloudflare claims authentication of every user and agent connection with identity-scoped least-privilege permissions.
Authenticate every user and agent connection
Cloudflare materials reviewed did not provide a public claim for controlling coding-agent commands, filesystem or network actions, skills, hooks, extensions, packages, or workstation activity.
No quoted source text is recorded for this claim.
Cloudflare AI Gateway claims token and cost logging, caching, cost-aware routing, rate limiting, usage controls, and unified billing.
token usage, cost, and duration
Cloudflare states that AI Gateway is available on all plans and that current core analytics, caching, and rate-limiting features are free.
AI Gateway is available to use on all plans.
Cloudflare positions AI security across its global network, SASE, application security, Zero Trust, developer platform, Workers, and major identity-provider integrations.
unified platform for securing workforce AI tools and public-facing applications