Shrinking the IAM Attack Surface through Identity Visibility and Intelligence Platforms (IVIP)
This article discusses the growing problem of ‘identity dark matter’ – unseen identity activity within enterprise systems due to fragmented IAM and a lack of visibility. Gartner has introduced the Identity Visibility and Intelligence Platform (IVIP) as a solution to address this issue, focusing on continuous discovery, data unification, and AI-driven intelligence. Orchid Security is highlighting its approach to operationalizing the IVIP by directly inspecting applications to uncover hidden identity risks.
The modern enterprise faces significant challenges with identity management, characterized by a fragmented landscape of applications, decentralized teams, and increasingly complex machine identities. This has led to ‘identity dark matter’ – a substantial portion of identity activity operating outside the visibility of traditional Identity and Access Management (IAM) systems. According to Orchid Security, approximately 46% of enterprise identity activity remains unseen, encompassing unmanaged applications, local accounts, and opaque authentication flows. This gap represents a critical security vulnerability, as organizations struggle to understand and control access to their systems. The rise of Agentic AI further exacerbates this problem, adding another layer of complexity and potential risk.
To combat this, Gartner proposes the Identity Visibility and Intelligence Platform (IVIP) as a foundational ‘System of Systems’ within the Identity Fabric. The IVIP provides an independent layer of oversight, leveraging AI-driven analytics to unify IAM data and deliver a single view of identity events and relationships. A credible IVIP must continuously discover identities across all systems, unify fragmented data from various sources, and translate scattered signals into actionable security insights. This includes capabilities like automated remediation, real-time signal sharing, and intent-based intelligence using LLMs.
Orchid Security’s approach focuses on directly inspecting applications to uncover hidden identity risks. Their solution utilizes binary analysis and dynamic instrumentation to examine native authentication and authorization logic without requiring APIs, source-code changes, or lengthy integrations. This allows them to identify and analyze identity activity across systems that traditional tools cannot see, revealing ‘identity dark matter’ such as local accounts and undocumented authentication paths. They unify proprietary audit telemetry with logs from centralized IAM systems to create a comprehensive, evidence-based identity data layer.