Notifications
Clear all
Topic starter
25/06/2026 1:21 am
TL;DR: Identity observability is emerging as the control layer that detects what IAM, IGA, PAM, and MFA miss by continuously correlating real identity activity across human, NHI, and agentic AI environments, according to AuthMind. It matters because policy-based access control cannot explain legitimate credentials used illegitimately, and that assumption no longer holds.
NHIMG editorial — based on content published by AuthMind: identity observability and the policy-to-behavior gap
By the numbers:
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
- Only 5.7% of organisations have full visibility into their service accounts.
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
Questions worth separating out
Q: How should security teams implement identity observability across human and non-human identities?
A: Start by covering the identities that can actually touch production, including users, service accounts, API keys, workload identities, and AI agents.
Q: Why do valid credentials still create breach risk when access is already approved?
A: Because approval proves only that access was granted, not that it was used safely.
Q: What do identity teams get wrong about identity visibility platforms?
A: Many teams assume a visibility platform is enough if it consolidates directories and policies.
Practitioner guidance
- Define the observable identity surface Inventory the human, NHI, and agentic AI identities that can authenticate, retrieve secrets, assume roles, or call APIs in production.
- Separate approval evidence from activity evidence Keep provisioning and certification workflows, but add live activity review for secret retrieval, role assumption, unusual hosts, and unexpected downstream access.
- Correlate identity context to network truth Require a monitoring approach that can tie access events back to observed traffic, workload behavior, and system origin.
What's in the full article
AuthMind's full blog post covers the operational detail this post intentionally leaves for the source:
- The platform's access-path mapping approach across cloud, network, SaaS, and IdP telemetry.
- The patent-backed method used to correlate identity activity with live dataflow signals.
- Operational examples of how anomalous secret retrieval and unexpected access paths are detected.
- Implementation detail on how automated remediation links detection to revocation and credential response.
👉 Read AuthMind's analysis of identity observability and the policy-to-behavior gap →
Identity observability and the governance gap teams are missing?
Explore further
25/06/2026 10:42 am
Identity observability is the control that closes the policy-to-behavior gap. IAM, IGA, PAM, and MFA govern what access should exist, but they do not continuously prove how that access is used after issuance. That leaves a structural blind spot where legitimate credentials can be abused without violating the provisioning record. The implication is that identity governance can no longer stop at approval and certification.
A few things that frame the scale:
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, according to Ultimate Guide to NHIs.
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures.
A question worth separating out:
Q: How can organisations tell whether identity observability is actually working?
A: Look for detection of behavior that is formally permitted but operationally wrong, such as unusual secret retrieval, an unexpected host, or a secret appearing on a second system. If the platform only reports static posture, it is not yet delivering identity observability.
👉 Read our full editorial: Identity observability exposes the gap between policy and behavior
