Enterprise AI Governance: Secure Access Control for Intelligent Agents
Entro Security Introduces Agentic Governance Administration (AGA) Platform
As enterprises increasingly adopt artificial intelligence (AI) agents and assistants, a new challenge has emerged: governing and controlling these AI-driven access points. To address this issue, Entro Security has introduced its Agentic Governance Administration (AGA) platform, designed to help security and identity teams regain control over AI agents and access across enterprise systems.
Addressing the Challenges of AI-Driven Access
The AGA platform is built on the principles of inventory, ownership, least privilege, auditability, and enforcement, which are fundamental to effective governance. However, the advent of AI-driven access has introduced a new access surface that traditional identity and access management (IAM) and identity governance and administration (IGA) tools are not equipped to handle.
In the context of AI agents, the user is often an AI service or locally running agent, and access paths are powered by non-human identities (NHIs), tokens, service accounts, API keys, and secrets. The blast radius of a security incident is defined by OAuth scopes, integrations, syncing, and automation, rather than a single human login.
AGA Platform Capabilities
The AGA platform builds a structured AI agent profile from three layers: sources, targets, and identities. Sources include endpoint telemetry, agent foundries, cloud environments where NHIs are used, and MCP servers. Targets include the enterprise assets and applications an agent touches, while identities include the human, non-human, or secret identities used to access those targets.
From this profile, AGA delivers two core capabilities: shadow AI discovery and AI agents monitoring and enforcement. Shadow AI discovery involves identifying AI clients and local agent runtimes on workstations, as well as agents being created in agent foundries and cloud service providers. This provides a single governed view of where an agent runs, what it can access, and which identities power it.
AI agents monitoring and enforcement involves providing visibility into MCP activity and policy enforcement, allowing teams to audit and govern agent behavior as it executes. This includes visibility into tools invoked and connected services, policy controls for sanctioned MCP targets and AI client behaviors, audit trails of allowed and blocked activity, and AI-focused controls to reduce sensitive data and secret exposure.
According to Itzik Alvas, CEO of Entro Security, “Enterprise AI adoption often starts with a connection, rather than a strategy. A developer connects a tool to an LLM, a team installs an AI app in SaaS, or someone authenticates an agent against SharePoint, GitHub, Salesforce, or internal APIs. AGA helps teams regain clarity and control as AI access becomes the default.”
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