Based on responses from more than 200 enterprises, the findings show how AI agents are reshaping identity attribution and access control in ways existing models were not designed to handle.
Zero-trust architecture is a security framework built on a simple premise: no user, device or workload should be trusted by default, regardless of where it sits on the network.
Agentic AI guardrails are the technical controls, policy frameworks, and oversight mechanisms that define what an AI agent can do, what it can access and when it needs to stop and ask a human.
Most organizations still treat credentials as something that must be protected, stored, and rotated. But a second model is quietly reshaping how machine authentication works: eliminate static secrets altogether and authenticate workloads using identity and just-in-time access.
Details shared by the attacker suggest the intrusion expanded beyond the initial application through permissions that allowed access to dozens of internal credentials.
Discover verifiable agentic AI deployments in software, security, IT Ops, and logistics. Learn the essential security, identity, and governance patterns for safe production use.
As agents scale and operate continuously, MCP servers are becoming long-lived access intermediaries, concentrating privilege in ways security teams have already struggled to contain.
A ServiceNow impersonation flaw illustrates how agentic systems turn weak identity assumptions into durable access paths across enterprise environments.
