RSAC session spotlights agentic AI for real-time threat hunting

In a blog post tied to its RSA Conference presence, Google Cloud describes how it is leaning on agentic AI to automate parts of the security operations workflow using live threat intelligence. Building on Mandiant’s incident and threat data and new partnerships such as Wiz, Google outlines agents that can read alerts, correlate them with frontline intelligence, decide which investigative playbooks to execute, and in some cases trigger containment or remediation actions.

While the post is positioned as a conference recap, it sketches an emerging archetype for high-stakes agents: systems that continuously reason over an evolving telemetry stream, call specialized tools (log search, network forensics, configuration management), and use policy constraints plus human approvals to perform impactful operations in production environments. Google also emphasizes the importance of validating these agents using realistic attack data—an implicit nod toward the need for better agentic evaluation and sandboxing frameworks in security.

What changed. Google Cloud publicly framed cybersecurity as a leading real-world domain for agentic AI, describing agents that combine threat intel with environment actions to drive semi-autonomous defense.

Why it matters. High-stakes domains like security force the agent ecosystem to mature fast on tool permissions, action logging, and behavior evaluation under adversarial pressure.

Builder takeaway. Even outside security, adopt similar patterns: define narrow tool scopes, enforce policy-based action gates, and test agents against realistic, adversarial scenarios before granting higher autonomy.