Microsoft named a Leader in the KuppingerCole Leadership Compass for Cloud Native Application Protection Platforms (CNAPP)
Source Microsoft Security Blog
Description
As organizations adopt AI, they must secure both cloud and AI environments through a unified security control plane as their attack surface expands. Because modern applications and AI workloads are built and run in the cloud, security teams must understand which exposures matter most, prioritize what can truly be exploited, and reduce risk across cloud infrastructure, applications, identities, data, and AI systems in one place. Modern IT estates now span multiple clouds and on-premises systems, with architectures built on containers, Kubernetes, serverless functions, microservices, APIs, and AI-powered workloads. This increases both the volume and the interconnectedness of security signals. The challenge is no longer identifying individual risks, but determining how misconfigurations, identities, and data exposures combine to create real attack paths, and which of these are most critical to fix at the source. KuppingerCole’s Leadership Compass: Cloud Native Application Protection Platforms (CNAPP) reflects this shift. The report describes how CNAPP is evolving from a consolidation of cloud security tools into the security foundation for AI-native enterprises, combining cloud security, AI security posture management, runtime protection, attack path analysis, cloud detection and response, and agentic AI operations into unified platforms. Read the full report Within this evolving market, KuppingerCole names Microsoft a Leader across all four of its Leadership categories: Overall, Product, Innovation, and Market. In the report’s words: “Microsoft earns its Overall Leadership with its Defender for Cloud that is redefining the CNAPP market by extending cloud security beyond infrastructure protection and into a unified security platform for cloud, data, identity, AI, and security operations, supported by one of the industry’s most advanced agentic AI ecosystems.” That recognition reflects where the category is heading: toward platforms that unify cloud and AI security into one operational view of risk. Why CNAPP is being redefined KuppingerCole makes a clear point: CNAPP is no longer about posture or visibility alone. It is becoming the operational foundation for securing AI-powered applications, services, and business processes, across the full software lifecycle from cloud infrastructure to the AI systems running on top of it. Modern environments introduce complexity across: Multicloud and hybrid infrastructure. Rapid development and continuous deployment. Containers, serverless, microservices, and APIs. AI models, agents, pipelines, and machine identities. This complexity exposes the limits of traditional, siloed tools, where cloud posture, workload protection, AI security, and the security operations center (SOC) each live in their own console. Organizations now need platforms that can: Correlate posture, runtime, identity, data, application, and AI signals. Prioritize risk based on exploitability, not severity alone. Integrate security across development, cloud operations, and the SOC. Bring AI systems into the same risk model as the rest of the cloud. Runtime intelligence is now central to this shift. Across the platforms KuppingerCole evaluated, 94% detect active exploitation of the complex attack paths they surface, moving teams from long lists of findings to the exposures threat actors can actually use. What distinguishes leading platforms KuppingerCole evaluates providers on product strength, innovation, and market presence, and, more importantly, on how effectively they help organizations manage real risk across cloud and AI. Several themes define the next generation of platforms: AI security posture management that governs models, pipelines, and AI-specific attack paths. Agentic AI that investigates, validates exposures, and helps remediate, not just detect. Runtime-driven risk prioritization focused on what is exploitable in production. Security graphs and attack path analysis across identity, data, network, workload, an…