Trend Micro Cloud Report 2025

Keypoints

• Annual cloud security reports typically begin with an overview of the research scope, participant base, and main conclusions, then move into sections on threat trends, incident response, compliance, strategic priorities, and emerging technologies such as AI.
• These reports usually combine executive takeaways with detailed findings, including survey percentages, year-over-year shifts, and practical guidance for security leaders.
• In this report, 512 cybersecurity professionals across Europe were surveyed, with a 95% confidence level and a ±4.1% margin of error.
• The central theme is a contradiction between escalating threats and lagging defenses: cloud environments are becoming more complex, but visibility, tooling, and response processes are not keeping pace.
• Ransomware was the top advanced threat concern at 74%, followed by zero-day vulnerabilities at 63% and privilege escalation or insider threats at 57%.
• Foundational cloud incidents remain common, including unauthorized access at 64%, data security concerns at 62%, and phishing or social engineering at 60%.
• API exposure is now a major concern at 52%, showing that interfaces and integrations have become a key attack surface in modern cloud architectures.
• Security leaders also worry about provider dependency at 41%, disaster recovery at 37%, shadow IT at 45%, and supply chain compromise at 37%, indicating that cloud risk spans operational, governance, and resilience issues.
• Only 21% of organizations report strong visibility across workloads, configurations, and data flows, which the report identifies as a foundational weakness affecting both prevention and response.
• Seventy-five percent of organizations have only moderate or low confidence in their ability to detect and prevent advanced threats, showing a major detection confidence gap.
• Root cause analysis is the most time-consuming part of incident response for 34% of respondents, while 21% say coordinating response across teams is the biggest time sink.
• A striking 97% say it is difficult to execute a unified response across multiple cloud providers, reflecting fragmented tooling and inconsistent telemetry.
• Automation is viewed as the biggest incident-response improvement by 36% of respondents, but only 52% currently prioritize it, revealing a clear strategy-execution gap.
• Compliance is increasingly treated as an operational discipline rather than a periodic audit task, with 73% prioritizing automated compliance monitoring.
• The main compliance barriers are tool complexity at 63%, limited automation at 58%, weak threat detection at 55%, and DevOps integration friction at 37%.
• Security priorities are converging on foundational controls: data security and privacy lead at 83%, identity and access management at 77%, and threat detection and response at 72%.
• Only 52% prioritize security automation and orchestration, suggesting that many teams still struggle to translate priorities into scalable execution.
• AI is no longer experimental in cloud defense; it is being operationalized for threat detection at 75%, anomaly analysis at 70%, and automated response at 62%.
• Explainable AI is the most valued AI/ML technique at 66%, indicating that trust, transparency, and auditability matter as much as raw detection power.
• Other promising AI approaches include deep learning for anomaly detection at 63%, natural language processing for phishing detection at 57%, and federated learning at 52%.
• AI’s most significant benefits are enhanced threat detection at 79%, faster incident response at 75%, reduced false positives at 73%, and alleviation of cybersecurity staffing shortages at 68%.
• The report’s recurring takeaway is that cloud security is shifting from point tools and manual workflows toward integrated platforms that unify visibility, policy enforcement, detection, and automated response.
• The recommended best practices are continuous identity enforcement, automated high-risk response paths, unified visibility, continuous compliance, reduced tool sprawl, and targeted AI use cases that directly improve action and speed.