TrendAI, the enterprise AI security leader from Trend Micro announced a collaboration with Anthropic to support the expanded deployment of Claude Opus 4.7 for security research. Through this collaboration, organizations can reduce real-world risk faster: leveraging AI-accelerated threat intelligence to identify, prioritize, and mitigate exploitable vulnerabilities before they impact the business.
TrendAI is participating in Anthropic’s Cyber Verification Program, which provides credentials to engage in the defensive use of frontier AI models.
TrendAI launched AESIR (AI-Enhanced Security, Intelligence, and Research), an AI-powered internal security research platform that combines machine-speed automation with human expert oversight, in 2025. AESIR uses Claude Opus 4.7 to reason like an attacker, determining what’s reachable, what’s controllable, and what’s exploitable across complex software ecosystems. At scale, this means autonomously discovering and proving real vulnerabilities. TrendAI Vision One builds on these insights by prioritizing, mapping attack paths, and enabling swift mitigation—including virtual patching—across hybrid environments.
TrendAI is operating at the intersection of the two most critical dynamics in cybersecurity today: the AI models driving the new threat landscape, and the AI-powered defenses needed to match them. AESIR has already uncovered and, with TrendAI ZDI, collaborated on patching for critical CVEs across industry-leading AI platforms including NVIDIA, Tencent, agentic frameworks, and MCP tooling. The TrendAI State of AI Security Report projects between 2,800 and 3,600 AI CVEs in 2026 alone; AESIR was built precisely to operate at that scale.
The collaboration between TrendAI and Anthropic pushes the industry forward by combining AI-driven code intelligence and real-world risk prioritization. The ability to determine which vulnerabilities pose real-world risk, prioritize them, and mitigate them before they are exploited has become critical. With TrendAI Vision One, organizations can operationalize findings by determining asset exposure, identifying attack paths, and applying controls like virtual patching and exploit detection. This reduces risk quickly, even when code fixes require more time. This is crucial for production environments, where vulnerabilities are often discovered after deployment.
