AI Agent Credentials Need a Five-Point Inventory Framework

The credential blind spot in AI agent deployments

Organizations are deploying AI agents with access to critical enterprise systems, but the credentials powering those agents rarely undergo the same scrutiny as human accounts. Roy Katmor, co-founder and CEO of Orchid, outlined this emerging security gap in a recent video presentation, according to Help Net Security.

The problem stems from how agents are provisioned. Teams approve the agent's function and the AI studio platform, but the underlying identities—OAuth tokens, API keys, service accounts, or repurposed human credentials—sit outside traditional identity governance workflows. As agents connect to more tools, permissions accumulate beyond their original scope.

Five elements every AI agent inventory should track

Katmor illustrated the issue with an onboarding agent that touches HR systems, identity providers, ticketing platforms, payroll, and internal applications. Each integration creates a new credential with its own permission set.

He recommends treating each AI agent as an application and maintaining an inventory with five core elements:

Owner and purpose: Document who is responsible for the agent and what business function it serves.

Tool access: List every enterprise system the agent can reach.

Credential types: Identify whether the agent uses OAuth tokens, API keys, service accounts, or borrowed human credentials.

Effective authority: Map the actual permissions granted across all connected systems, not just the intended scope.

Runtime behavior: Monitor what the agent actually does with its access in production.

This inventory enables teams to compare approved intent against observed behavior and implement scoped controls, including targeted kill switches for specific agents without disrupting other systems.

Why it matters

AI agents represent a new category of non-human identity that doesn't fit cleanly into existing identity and access management frameworks. Unlike service accounts that typically connect two systems, agents may interact with dozens of tools, accumulating permissions that create lateral movement risks if compromised. Without systematic tracking, organizations lose visibility into which credentials exist, what they can access, and whether their runtime behavior matches their documented purpose—the same visibility gaps that have enabled major breaches through compromised service accounts.

Moving from approval to continuous oversight

The shift from approving an agent once to continuously monitoring its credential footprint represents a fundamental change in how enterprises should approach AI security. As agents become more autonomous and handle more sensitive operations, the credentials behind them become high-value targets.

Details of the framework were first reported by Help Net Security.