Entro has officially launched Agentic AI Security as the third pillar of its platform, building upon their foundation in secrets management and non-human identity (NHI) protection and "for the first time, enterprises can unify the security of secrets, NHIs, and agents into one risk ecosystem from a single solution." (source)
Closing the Control Gap in Agentic Systems
AI agents are now central to automation, decision-making, and operational efficiency across industries. Yet their rapid spread introduces an equally rapid expansion of unmanaged identities and credentials. These autonomous systems generate and consume secrets, assume permissions, and act on behalf of users, often without visibility from traditional Identity and Access Management (IAM) or vault solutions.
Entro’s new capability directly addresses this gap. With Agentic AI Security, the company extends its discovery and protection coverage to include AI agents themselves, detecting them across cloud, SaaS, development, and code environments, linking each one to the secrets and NHIs it uses, and assigning human ownership for accountability.
By connecting these elements within a single lifecycle, Entro provides enterprises with continuous observability and the ability to detect privilege misuse or misconfiguration in real time. The platform enforces least privilege for agents, automates credential rotation, and supports incident response with rapid correlation between secrets, agents, and entitlements.
A New Lifecycle Model for AI Adoption
Entro describes Agentic AI Security as the natural evolution of its existing architecture, designed to manage the intersection of NHIs, secrets, and now AI agents. The company’s approach is based on the premise that these three asset types cannot be secured in isolation. Each is dependent on the other: secrets grant access, identities define scope, and agents operationalize both.
This interconnected lifecycle introduces new risks if any layer is left unmonitored. An AI agent that stores or shares secrets outside authorized channels, for example, can easily bypass policy boundaries. Entro’s integrated model prevents such exposures by tracking every credential used by an agent and correlating its activity with known NHIs and human owners.
The company positions this unified model as a way to safeguard AI innovation without constraining it. Rather than restricting the deployment of autonomous tools, it enables security teams to maintain control and auditability while supporting business agility.
Defending Against Emerging AI Risks
As organizations accelerate their use of generative and agentic systems, non-human identities have outpaced human users by orders of magnitude. Each of these digital actors represents a potential point of compromise, especially when their secrets are stored insecurely or when agents act without human oversight.
Entro state how standards such as Model Context Protocol (MCP) have accelerated adoption as "engineering teams have democratized a new super-tool: AI agents. At unprecedented speed, agents are compounding the very risks we set out to solve, multiplying NHIs, amplifying entitlements, and exposing secrets at an unprecedented pace."
These autonomous entities can multiply themselves, consume secrets, and create entitlements faster than existing tools can track, exposing organizations to credential sprawl and lateral movement risk.
Traditional IAM and vault systems were built for static entities, servers, applications, or service accounts with predictable behaviors. Agentic AI, in contrast, is dynamic and self-directed. Without visibility, enterprises face an expanding class of “shadow agents,” capable of acting beyond the boundaries of existing policy. The platform mitigates this through continuous monitoring and correlation, ensuring every action taken by an AI agent is attributable and governed.
Designed for Enterprise Scale and Real-Time Defense
The architecture scales across multi-cloud and hybrid environments, integrating with telemetry and discovery feeds to identify every credential and agent relationship. The system’s NHIDR (Non-Human Identity Detection and Response) engine drives real-time analytics, surfacing anomalies that indicate unauthorized privilege escalation or misuse.
Through this detection layer, Entro provides both preventive and responsive capabilities. Preventive controls ensure that new agents inherit the appropriate access boundaries from inception. Responsive controls, meanwhile, detect deviations, such as an agent accessing secrets outside its assigned scope, and can automatically trigger remediation or alert workflows.
The Strategic Implication for CISOs
The message for CISOs and enterprise architects: AI agents represent a new and fast-evolving identity class that must be governed as rigorously as any human account. Entro’s launch provides an advancement in closing the control gap between automation and security.
With Agentic AI Security, enterprises gain a lifecycle-based defense model that anticipates how AI will reshape identity and access management. It is not simply about protecting credentials; it is about extending governance and accountability into the autonomous systems that now form the backbone of digital operations.