Company context
Public-company product under Tenable (NASDAQ: TENB)
Tenable completed the Apex acquisition in Q2 2025 and is integrating AI exposure into Tenable One
Vendor research
Apex Security / Tenable
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.
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.
- $999.4M annual revenue (2025-12-31)
- 1000+ employees
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 16
- Evaluation requirements
- 19 in this research model
- Unresolved requirements
- 3
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.
Founded2023
HeadquartersApex origins in AI security startup ecosystem; current product under Tenable, Columbia, Maryland
OwnershipPublic-company product under Tenable (NASDAQ: TENB)
Employees1000+
Capital and scaleOwned business
Tenable
- Latest annual company revenue
- $999.4M
- Current owner annual revenue
- $999.4M
- Operating scale
- Tenable completed the Apex acquisition in Q2 2025 and is integrating AI exposure into Tenable One
- Backing context
- Formerly VC-backed with early investor interest from Sequoia Capital, Index Ventures, Sam Altman, and Clem Delangue; public sources reviewed did not confirm an Apex round amount; acquired by Tenable
Tenable Holdings, Inc. · period ended 2025-12-31 · filed 2026-02-27
Tenable Holdings, Inc. (TENB) · period ended 2025-12-31 · filed 2026-02-27
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
- 2023
- 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 sourceTenable acquisition announcementTenable announced intent to acquire Apex, described Apex as founded in 2023, and listed early investors.Company sourceTenable Q2 2025 resultsTenable's Q2 2025 results state it completed the acquisition of Apex Security.Company information sourceStored company websiteSupports the company facts shown in this profile.Regulatory filing10-K annual filingTenable Holdings, Inc. (TENB) · 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
- Buyer diligence should treat Apex as Tenable One AI Exposure rather than a standalone startup procurement.
- Public claims may be most relevant where exposure management, asset context, and AI risk need to be viewed together.
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 referenceCIS Critical Security Controls
- Requirements with public support
- 15
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 15
- 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
- 11
- References
- 27
- Requirements with public support
- 15
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 15
- 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
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
Limited 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
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
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
No supporting claim foundPublicly 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.
Tenable One AI Exposure claims continuous AI discovery, risk-aware inventory, owner and access context, acceptable-use policy, compliance support, exposure prioritization, remediation, and agent isolation across applications, infrastructure, identities, agents, and data.
Enforce AI acceptable-use policies and support compliance with emerging industry standards, including the NIST CSF and EU AI Act.
Tenable AI Exposure and AI-SPM materials reviewed did not provide a public customer-facing product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.
No quoted source text is recorded for this claim.
Tenable claims discovery and vulnerability analysis for AI software components, packages, browser extensions, model repositories, third-party tools, integrations, workloads, and dependencies across cloud and enterprise AI environments.
Detect AI-related packages in systems and web applications, along with browser extensions, associated vulnerabilities, data leakage and unauthorized resource consumption.
Tenable One AI Exposure claims detection and stopping of prompt injection and jailbreaks, containment and isolation of risky agents, policy enforcement for unsafe tools and actions, and monitoring of AI interactions and data flows.
Detect and stop AI-specific attacks such as prompt injection and jailbreak attempts, and contain risky or compromised AI agents.
Tenable claims agent ownership and access inventory, identity and entitlement correlation, least-privilege remediation, risky permission detection, and agent isolation or access-level changes.
View agent owner, access level, tools, knowledge, and isolate the agent from the agent details panel.
Tenable claims discovery and risk analysis for AI tools on endpoints, developer libraries, packages, browser extensions, agents, code repositories, model repositories, build environments, and unsafe third-party integrations.
Continuously discover and monitor all AI usage across your organization, including shadow AI, agents, browser plug-ins, and more.
Show 13 additional evidence records
Tenable AI Exposure and AI-SPM materials reviewed did not provide a public product claim for AI usage-cost attribution, token or spend metrics, budgets, chargeback, or cost-aware model routing.
No quoted source text is recorded for this claim.
Tenable One AI Exposure claims a single risk-aware perspective of AI tools and usage, cloud infrastructure, and identities for the invisible attack surface created by shadow AI, hidden attack paths, and data leaks.
Close your AI exposure management gap and uncover the invisible attack surface that shadow AI, hidden attack paths, and data leaks create. Get a single, risk-aware perspective of all your AI tools and usage, cloud infrastructure, and identities.
Tenable One AI Exposure publicly lists supported AI platforms including ChatGPT Enterprise, Microsoft Copilot, 365 Copilot, and Studio Copilot.
Tenable One AI Exposure currently supports these AI platforms: OpenAI ChatGPT Enterprise, Microsoft Copilot, 365 Copilot, and Studio Copilot.
Tenable One AI Exposure claims visibility into how employees and agents use approved AI platforms, including intent, usage patterns, and exchanged data.
Understand how employees and agents use approved AI platforms, including intent, usage patterns, and the data they exchange, so you can identify AI risks early, before exposure occurs.
Tenable One AI Exposure claims prioritized actions to fix AI misconfigurations, enforce AI acceptable-use policies, and reduce AI exposure.
Take action with prioritized insights to fix AI misconfigurations, enforce AI acceptable use policies (AI AUP), and reduce AI exposure.
Apex (Tenable) claims it uncovers AI-specific misconfigurations, risky integrations, and exposed services that traditional data loss prevention (DLP) and cloud access security broker (CASB) tools miss.
Uncover AI-specific misconfigurations, risky integrations, and exposed services that traditional tools like DLP and CASB miss
Tenable One AI Exposure claims it detects and stops AI-specific attacks and contains risky or compromised AI agents.
Detect and stop AI-specific attacks such as prompt injection and jailbreak attempts, and contain risky or compromised AI agents before they cause damage.
Apex Security / Tenable AI Exposure inventories AI agents and surfaces their attack surfaces, trust models, and governance challenges within an organization.
introduces new attack surfaces, trust models, and governance challenges
Apex Security / Tenable claims AI-agent exposure management with visibility into agents, connected applications, identities, permissions, and data access.
connecting AI software, cloud infrastructure, identities, and usage into a single, risk-aware view
Apex (Tenable) claims it shows how employees and agents interact with AI platforms, including who is using AI, for what purpose, and the data involved.
See how employees and agents interact with AI platforms, including who’s using AI, for what purpose, and the data involved.
Apex (Tenable) claims it detects and stops AI-specific attacks including prompt injection and jailbreak attempts.
Detect and stop AI-specific attacks such as prompt injection and jailbreak attempts
No public claim found for this capability.
No quoted source text is recorded for this claim.
Apex (Tenable) claims it manages risk across approved AI platforms via a unified exposure-management layer integrating multi-vendor model usage.
Bring AI exposure data into Tenable One to see AI risk in context with other cyber threats across IT, cloud, identity, and OT.