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25/06/2026 10:28 pm
TL;DR: The deeper issue is that policy intent and runtime identity behaviour are diverging faster than conventional IAM visibility can reconcile, according to AuthMind research, whose latest patent covers monitoring network dataflows and authentication activity to identify compromised AI agents, unauthorized access paths, and other identity-related threats across cloud, SaaS, and hybrid environments.
NHIMG editorial — what this means for AI and NHI governance
Questions worth separating out
Q: How should security teams govern identities when access and behaviour no longer match?
A: Teams should treat runtime behaviour as the control signal and entitlements as only one input.
Q: Why do AI agents and machine identities create visibility gaps in IAM programmes?
A: Because they often act through delegated credentials, chained tools, and short-lived sessions that are easy to approve but hard to observe in context.
Q: What breaks when identity governance relies only on access reviews?
A: Access reviews assume the reviewable state is a stable entitlement that reflects real risk.
Practitioner guidance
- Correlate entitlements with runtime activity Join IAM, network, and authentication telemetry so reviewers can compare approved access with observed behaviour across cloud, SaaS, and hybrid systems.
- Instrument AI agents as first-class identities Assign each agent a traceable runtime identity, then log tool use, downstream requests, and access path changes in a way that supports attribution.
- Hunt for shadow identities and unapproved access paths Look for identities that appear in activity logs without a corresponding governance record, especially where machine credentials or agent workflows span multiple systems.
What's in the full announcement
AuthMind's full press release covers the patent language and product framing this post intentionally leaves to the source:
- The formal scope of U.S. Patent No. 12,615,283 B2 and how the vendor describes its claims.
- The vendor's explanation of Identity Access Flow Graph technology and how it maps identity activity.
- Additional product-context language on identity observability, ITDR, and ISPM that this post does not evaluate in detail.
- The full announcement text and company positioning around agentic AI runtime security.
👉 Read AuthMind's patent announcement on identity observability and AI-driven risk detection →
Identity observability for AI agents and NHIs: what changes now?
Explore further
25/06/2026 11:00 pm
Identity observability is becoming a control requirement, not a monitoring enhancement. The patent announcement reflects a broader market reality: policy-only IAM does not tell teams whether an identity is using access in ways that create risk. That matters across AI agents, NHIs, and human accounts because the exploit path increasingly lives in behaviour, not just entitlements. Practitioners should treat runtime identity visibility as a governance control that closes the gap between approval and action.
A few things that frame the scale:
- The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
- Only 44% of developers are reported to follow security best practices for secrets management, which helps explain why runtime identity problems keep recurring after policy approval.
A question worth separating out:
Q: How do organisations know whether identity observability is actually working?
A: They should be able to reconstruct the real access path for a suspicious identity event, identify the exact credential or agent involved, and show whether the observed behaviour matched policy. If they cannot trace that sequence, observability is incomplete and the control is not yet effective.
👉 Read our full editorial: Identity observability patent signals a wider gap in AI governance
