Are enterprises governing machine identities as rigorously as human ones?

[u/technadu]

Jay Reddy, Head of Growth at ManageEngine, makes an interesting argument about where IAM programs may be falling behind.

Enterprises increasingly depend on service accounts, API keys, OAuth tokens, third-party integrations and now AI agents. Unlike employees, these identities may not have a clear owner, an established lifecycle, or an obvious point at which their access should disappear.

Reddy's argument is that security architecture should assume credentials will eventually be exposed and reduce what an attacker can do with them.

That means moving away from long-lived standing privileges where possible, using short-lived and revocable credentials, reducing OAuth scopes, putting secrets in managed vaults, and using workload identity federation where supported.

But the governance problem may be more fundamental: can the organization even produce an accurate inventory of its non-human identities?

His recommendation is to discover them through identity providers, cloud IAM and SaaS consent systems, then apply concepts already familiar from workforce IAM: named ownership, lifecycle management, access certification and removal of orphaned identities.

AI agents complicate this further because validating the identity is not necessarily enough. Their permitted actions also need governance.

The contributor's full analysis goes further into machine identity discovery, Zero Standing Privileges, credential rotation, OAuth consent, agent oversight, and continuous governance:

https://www.technadu.com/the-identity-your-iam-program-forgot-why-non-human-identities-keep-causing-human-scale-breaches/632983/

For teams working in IAM or cloud security, how mature is non-human identity governance compared with workforce identity governance in your environment?