CRN’s 2026 Cloud 100 names 20 cloud-security companies spanning CNAPP, data security, identity, AI protection, developer security, networking, detection and response, and managed security. The list is an editorial selection—not a ranked test, market-share table, independent benchmark, or universal buying recommendation. Its value is as a map of the companies shaping cloud security in 2026.
That distinction matters. Wiz, Snyk, Cyera, Illumio, Zscaler, and WatchGuard may all appear on the same list, but they address very different security problems. The right shortlist depends on what an organization needs to protect, how much runtime visibility it requires, which clouds and applications it uses, and whether it wants a broad platform or a specialist tool.
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Why cloud security is expanding in 2026
Cloud security now covers far more than checking whether a storage bucket is public. Security teams are also trying to protect identities, containers, Kubernetes clusters, source code, SaaS applications, sensitive data, AI models, AI agents, developer workflows, and cloud-connected networks.
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CRN cited CrowdStrike research reporting that cloud intrusions increased 136% in the first half of 2025 compared with all of 2024, with China-linked attackers accounting for 40% of the increase. Those figures are vendor-reported research findings, not an independent measurement of every cloud intrusion.
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The companies on CRN’s list reflect that expansion. Some are broad cloud-native application protection platform (CNAPP) providers. Others focus on data security posture management (DSPM), secure access service edge (SASE), vulnerability management, segmentation, cloud forensics, application security, or managed detection and response.
See CRN’s original selection: The 20 Coolest Cloud Security Companies of the 2026 Cloud 100.
How to read the categories
- CSPM and exposure management: Discover cloud assets, identify misconfigurations, map attack paths, and prioritize exposures.
- CNAPP: A broad category that may combine posture management, workload protection, identity analysis, infrastructure-as-code scanning, container security, software composition analysis, detection, and runtime controls. Vendors use the term inconsistently.
- DSPM: Finds sensitive data, maps where it resides and who can access it, and highlights exposure across cloud and SaaS environments.
- AI security: May include AI asset discovery, model scanning, prompt-injection protection, AI data-loss prevention, training-data protection, agent security, or safeguards for AI-generated code.
- Cloud detection and response: Detects suspicious activity and supports investigation, containment, and response in cloud environments.
- SASE and zero trust: Controls user access to applications, private networks, SaaS services, websites, and cloud resources through cloud-delivered security services.
- Application and code security: Scans source code, dependencies, containers, and infrastructure-as-code during development.
Several vendors belong in more than one category. “AI security” is particularly fluid: AI-SPM, AI runtime protection, AI data security, AI governance, and agent security are overlapping but not interchangeable labels.
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Broad cloud and CNAPP platforms
1. Wiz
Wiz represents cloud-native exposure management and CNAPP. Its platform is positioned around fast, broad visibility across infrastructure, applications, identities, data, and cloud attack paths. CRN highlighted Wiz’s MCP Server for cloud visibility and investigation and Wiz Code SAST for proprietary-code analysis.
Likely buyer: Cloud-first enterprises wanting a unified view of risk without deploying agents everywhere.
Qualification: Buyers should separately evaluate remediation, runtime prevention, workload instrumentation, developer adoption, and the telemetry lost when agents are not deployed. Enterprise pricing is quote-led.
2. Orca Security
Orca Security is an agentless cloud-security and CNAPP specialist covering posture, workloads, data, and AI security. CRN pointed to expanded AI-SPM capabilities for risks involving sensitive AI training data in cloud-native environments.
Likely buyer: Security teams seeking rapid cloud discovery and broad coverage with limited agent deployment.
Qualification: Agentless discovery does not automatically provide deep process, kernel, file, or runtime telemetry. Confirm where agents or complementary controls are required.
3. Palo Alto Networks
Palo Alto Networks is consolidating cloud posture, application security, detection, and response under Cortex Cloud, positioned as the successor to Prisma Cloud.
Likely buyer: Large enterprises seeking consolidation across cloud security, network security, and security operations.
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4. CrowdStrike
CrowdStrike connects cloud workload security with endpoint, identity, detection, and response capabilities in the Falcon platform. CRN highlighted AI model scanning, an AI security dashboard, runtime cloud data protection, GenAI data protection, and reported pay-as-you-go Falcon Cloud Security availability through AWS Marketplace in December 2025.
Likely buyer: Organizations already using or considering the broader Falcon security platform.
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Qualification: Value may be lower if a buyer does not want to standardize on a broad endpoint, identity, and cloud-operations ecosystem. Confirm current marketplace terms.
5. Fortinet
Fortinet combines network, secure-access, identity, operations, and cloud security. CRN cited FortiCloud expansion, FortiIdentity, and Lacework FortiCNAPP capabilities including real-time CloudTrail alerting.
Likely buyer: Enterprises and channel partners already invested in Fortinet appliances or the Fortinet Security Fabric.
Qualification: Verify the depth of cloud-native developer workflows, infrastructure-as-code controls, and runtime capabilities for the specific deployment.
6. Check Point Software Technologies
Check Point CloudGuard represents prevention-oriented enterprise network, cloud, application, and threat security. CRN highlighted AI Cloud Protect, including safeguards aimed at prompt injection and model exfiltration, and an integrated CNAPP combining CloudGuard with Wiz’s cloud-native platform.
Likely buyer: Large enterprises seeking cloud controls integrated with existing Check Point infrastructure.
Qualification: Buyers should determine whether they need Check Point’s unified platform approach or more specialized cloud-native tooling.
7. SentinelOne
SentinelOne extends endpoint and autonomous detection-and-response capabilities into cloud workload, identity, and AI security. CRN cited Singularity Cloud Security enhancements, Prompt Security for Employees following the Prompt Security acquisition, and integrations with AWS Security Hub and Amazon CloudWatch.
Likely buyer: Organizations seeking cloud and endpoint response through a common operational platform.
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8. Trend Micro
Trend Micro covers hybrid-cloud workloads, networks, endpoints, applications, and AI security. CRN highlighted an enterprise AI-security platform for protecting data and workloads across cloud, hybrid, and on-premises environments, linked to an NVIDIA Enterprise AI Factory validated design.
Likely buyer: Enterprises operating AI workloads across mixed infrastructure.
Qualification: Confirm which controls are native to Trend Micro, which depend on NVIDIA infrastructure patterns, and how the platform integrates with existing cloud-native tools.
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9. Cloudflare
Cloudflare is a cloud-delivered edge, application, access, and network-security provider rather than a conventional CNAPP-only vendor. CRN highlighted security posture management across SaaS applications, cloud infrastructure, email, and web assets, along with AI-SPM capabilities for visibility and policy enforcement around AI use.
Likely buyer: Organizations wanting connectivity, application security, zero trust, and edge protection through one globally distributed platform.
Qualification: Its strongest fit may be edge and access security, not deep cloud workload or developer security.
10. Netskope
Netskope focuses on SASE, CASB, zero trust, SaaS security, data protection, and DSPM. CRN highlighted DSPM enhancements supporting safer LLM training and better assessment of AI-related activity risk.
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Likely buyer: Enterprises controlling data movement through SaaS, web, private applications, and AI services.
Qualification: Netskope is not primarily a cloud-infrastructure posture or workload-runtime platform.
11. Zscaler
Zscaler represents zero trust, secure web access, SaaS protection, and cloud-delivered data controls. CRN highlighted AI-powered data classification across more than 200 categories and protections for Microsoft 365 Copilot and other generative-AI applications.
Likely buyer: Enterprises seeking to control user-to-application access and prevent sensitive-data leakage through cloud and AI services.
Qualification: Zscaler should not be treated as a full cloud-infrastructure posture or workload-security platform.
12. Cyera
Cyera specializes in DSPM and cloud data security. CRN highlighted AI Guardian, including AI-SPM and AI Runtime Protection, for discovering sensitive data and governing AI-related exposure.
Likely buyer: Organizations whose main problem is understanding where sensitive data resides, who can access it, and how AI uses it.
Qualification: Cyera is more data-focused than a broad CNAPP and may complement, rather than replace, CNAPP, DLP, SIEM, or identity tools.
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13. WatchGuard Technologies
WatchGuard is strongly associated with network security, firewalls, endpoint protection, managed security, and channel-delivered services. CRN highlighted FireCloud Internet Access, extending Firebox unified threat management to AWS and Microsoft Azure environments.
Likely buyer: Small and mid-market organizations, managed service providers, and existing Firebox customers.
Qualification: It is less suited to teams seeking deep cloud-asset graphs, infrastructure-as-code workflows, or specialist CNAPP functionality.
Exposure, vulnerability, and risk operations
14. Tenable
Tenable focuses on vulnerability and exposure management across infrastructure, identities, cloud, and AI. CRN highlighted Tenable AI Exposure, including AI discovery, exposure prioritization, governance, and security guardrails.
Likely buyer: Organizations wanting a unified view of exposure and risk-prioritization work.
Qualification: Exposure management identifies and prioritizes risk; it does not by itself provide every prevention or runtime-response control.
15. Qualys
Qualys represents asset inventory, vulnerability management, compliance, and risk operations. Its Enterprise TruRisk Management and Risk Operations Center combine asset data, threat intelligence, business context, and compensating controls. Qualys also supports managed Risk Operations Center services through partners.
Likely buyer: Organizations needing centralized vulnerability and risk prioritization at scale.
Qualification: Qualys is not principally an AI-native or cloud-only provider; its strongest fit is exposure and vulnerability operations.
Detection, response, containment, and forensics
16. Darktrace
Darktrace applies AI-assisted detection and response across network, email, identity, cloud, and enterprise environments. Following its acquisition of Cado Security, CRN highlighted automated cloud forensics and forensic acquisition capabilities.
Likely buyer: Security operations teams needing investigation and response across complex environments.
Qualification: Assess alert quality, investigation workflow, integrations, and how Darktrace fits with existing SIEM, SOAR, and cloud-posture tools. Product maturity and integration should be verified after an acquisition.
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Illumio represents segmentation, zero trust, breach containment, and cloud detection and response. CRN highlighted Illumio Insights, an agentless cloud detection-and-response product built on a security graph, with network-flow ingestion, traffic classification, risk discovery, and one-click containment.
Likely buyer: Organizations focused on limiting lateral movement and containing breaches across hybrid and multicloud environments.
Qualification: Illumio’s core value is containment and segmentation; it is not automatically a replacement for CSPM, vulnerability management, or full CNAPP functionality.
18. Sophos
Sophos combines endpoint, network, identity, security operations, and managed detection and response. CRN highlighted cloud identity threat detection and response following the Secureworks acquisition, including more than 80 cited cloud-identity posture checks and identity-attack detection.
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Qualification: Distinguish Sophos’s managed-service value from standalone CNAPP capabilities, and verify how Secureworks-derived functions are integrated.
Developer and AI application security
19. Snyk
Snyk focuses on developer security: open-source dependencies, source code, infrastructure as code, containers, and AI-assisted development. CRN highlighted the Snyk AI Trust Platform for AI-generated code and later described Evo as an agentic security-orchestration system. Those product claims should be treated as vendor or CRN descriptions, not independent efficacy findings.
Likely buyer: Development and application-security teams embedding controls into IDE, pull-request, and CI/CD workflows.
Qualification: Snyk is not a substitute for runtime cloud security, network protection, or SOC response.
20. OpenText Cybersecurity
OpenText Cybersecurity represents a broad portfolio spanning identity, application security, data security, threat detection, and governance. CRN highlighted an AI Data Platform intended to bring together structured and unstructured data, governance, contextual intelligence, orchestration, and security for AI data handling.
Likely buyer: Large organizations seeking a broad portfolio, particularly those with existing OpenText deployments.
Qualification: OpenText’s inclusion is broader and less narrowly cloud-native than that of specialist CNAPP companies. Buyers should evaluate the exact product and implementation scope rather than treating the portfolio as one product.
What buyers should compare
The most useful comparison is not a first-to-last ranking. It is a capability and operating-model assessment.
| Decision area | Questions to ask |
|---|---|
| Security domain | Does the product protect infrastructure, workloads, identities, SaaS, data, source code, AI models, user access, runtime activity, or security operations? |
| Deployment | Does it use cloud APIs, agents, network sensors, browser or endpoint agents, SaaS integrations, or developer-tool integrations? |
| Cloud coverage | Which AWS, Azure, Google Cloud, Kubernetes, serverless, private-cloud, hybrid, and AI services are actually supported? |
| Remediation | Does the tool provide visibility only, prioritization, tickets, suggested fixes, automated configuration changes, policy enforcement, runtime blocking, segmentation, or managed response? |
| Runtime depth | What telemetry is available without agents, and what process, file, network, kernel, or response capabilities require agents? |
| Developer workflow | Are IDEs, pull requests, CI/CD, infrastructure as code, containers, dependency reachability, ownership routing, and fix recommendations supported? |
| AI security | Does it discover models, inspect prompts and responses, protect training data, secure agents and tool calls, block sensitive data, or govern third-party AI applications? |
| Operations | Can findings connect to endpoint, identity, SIEM, SOAR, ticketing, CMDB, and managed-service workflows? Are APIs complete and logs exportable? |
| Commercial model | Is billing based on assets, workloads, users, identities, developers, data volume, log ingestion, cloud accounts, or modules? |
Important trade-offs
Consolidation versus specialization
A broad platform can reduce the number of vendors and integrations, but may provide less depth in a particular domain. A specialist may deliver stronger DSPM, code security, segmentation, or AI protection while adding operational complexity.
Posture management versus runtime protection
Finding a public storage bucket, excessive privilege, or vulnerable workload is not the same as preventing exploitation. Ask which controls are preventive, which are detective, and which support response after an attack begins.
Agentless versus agent-based security
Agentless approaches can speed inventory and reduce deployment friction. Agents can provide deeper process, file, network, and runtime telemetry. “Agentless” describes a deployment or discovery approach; it does not mean telemetry-free or universally sufficient.
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Native cloud controls versus third-party platforms
AWS, Microsoft Azure, and Google Cloud each provide native security services. Third-party platforms can correlate findings across clouds and provide a common workflow, but may duplicate native functionality and add licensing, ingestion, or implementation costs.
Acquisition and product-transition risk
Several entries have recently reshaped their portfolios through acquisitions or major product changes, including Darktrace and Cado Security, Fortinet and Lacework, Palo Alto Networks’ transition from Prisma Cloud toward Cortex Cloud, SentinelOne and Prompt Security, and Sophos and Secureworks. Verify road maps, migration requirements, contract treatment, support boundaries, and whether acquired capabilities are fully integrated.
How to shortlist the list for different needs
- Fast cross-cloud visibility: Start with agentless CNAPP specialists such as Wiz or Orca Security, then assess whether runtime controls require agents.
- Developer and application security: Evaluate Snyk and the application-security modules of broader platforms. Check IDE, pull-request, CI/CD, IaC, container, and dependency workflows.
- Data discovery and AI-data governance: Consider Cyera, Netskope, or Zscaler according to whether the priority is cloud data inventory, SaaS and user activity, or access and data-loss controls.
- Segmentation and containment: Consider Illumio, especially where limiting lateral movement is more urgent than replacing posture management.
- Managed detection and response: Compare Sophos, CrowdStrike, SentinelOne, Darktrace, and relevant channel partners based on service scope, escalation, telemetry, and response authority.
- Network and cloud controls together: Consider Check Point, Fortinet, Cloudflare, WatchGuard, or Zscaler based on the existing network and access architecture.
- Exposure and vulnerability prioritization: Evaluate Tenable or Qualys when asset inventory, vulnerability context, compliance, and risk operations are central.
- AI-heavy development: Examine separate controls for model and data discovery, prompt and response inspection, agent and MCP security, AI-generated code, and runtime protection. No single “AI security” label proves that all of these are covered.
Questions to ask during a proof of concept
- What assets, identities, data stores, workloads, models, agents, and applications are discovered automatically?
- How long does it take to obtain useful coverage, and what setup work is required?
- Which findings are demonstrably exploitable or attack-path relevant rather than merely misconfigured?
- Can the product connect identity, data, workload, application, and network relationships?
- What can it remediate automatically, and what approval or rollback controls exist?
- What telemetry is unavailable without agents?
- How does it handle ephemeral workloads, serverless functions, containers, and short-lived cloud identities?
- How does it secure AI models, agents, prompts, tool calls, training data, and MCP connections?
- Can it export findings to the existing SIEM, SOAR, ticketing, CMDB, and developer systems?
- What is the billing unit, and what costs apply to data volume, logs, APIs, users, workloads, or cloud accounts?
- Which features are generally available, regionally limited, preview-only, or dependent on an acquired product?
- What data is retained, where is it stored, and what happens to access and data when the contract ends?
Bottom line
CRN’s 20-company list is best understood as a market map, not a buying ranking. It shows how cloud security in 2026 has expanded into data, identity, AI, code, access, runtime protection, containment, and managed response.
For a real purchase decision, first identify the security layer and operational outcome you need. Then compare coverage, deployment model, runtime depth, remediation, integrations, AI scope, partner delivery, product maturity, and billing. A broad platform may simplify operations; a specialist may solve a narrower problem more deeply. Neither approach is automatically right for every organization.
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