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The 2026 Cyber Risk Report builds on last year's findings with expanded telemetry, providing organizations with the directional insights and data that can be used to help prioritize the exposures that matter most before attackers reach them.

Rethink endpoint security for the AI era. Endpoints now converge users, identities, data, and AI, increasing risk from shadow AI and advanced attacks. This demands stronger visibility, correlation, and resilience.

Claude Mythos Preview shows how AI can rapidly discover and weaponize zero-day vulnerabilities—transforming once human-scale threats into machine-speed attacks. As these capabilities spread, public sector organizations must rely on trusted, proactive defenders like TrendAI™ ZDI to stay ahead of an AI-driven threat landscape.

TrendAI™ Research analyzed 2,014 enterprises throughout 2025 and found that cyber damage is shaped by the interaction of attack pressure and exposure, with the highest-risk organizations experiencing up to 3.3 times as much damage as the lowest. The study introduces a Cyber Risk Positioning Map that can help organizations identify whether to prioritize reducing exposure, strengthening response capability, or both.

In this research, we analyzed over 19,000 open-source MCP server repositories to uncover how much AI-generated code they contain and how many harbor exploitable vulnerabilities.

Organizations are rapidly connecting AI agents to their databases, document pipelines, and internal tools, creating privileged components that read untrusted input as part of their job. TrendAI™ Research examines how attackers turn these agents against you through return-to-tool (RTT) exploits, and what this means for the future of agentic AI security.

TrendAI™ and CleanDNS have partnered to go beyond blocking malicious domains. Learn how we are actively dismantling the infrastructure that cybercriminals depend on and removing attacker domains from the internet before attacks reach their targets.

Analysis from TrendAI™ Research found that thousands of DICOM medical imaging servers worldwide are exposed online without basic security measures, leaving sensitive patient data and healthcare operations vulnerable to cyberattacks.

Exposed Model Context Protocol (MCP) servers have become powerful vectors for cloud attacks, enabling threat actors to not only access sensitive data but also take control of the cloud services themselves.