Topic starter
14/08/2025 12:12 pm
TL;DR: Manual approvals and rule-based JIT still leave enterprises exposed to standing privilege risk because they ignore context, behavior, and compromise signals, while AI-driven dynamic JIT can reduce friction and tighten least privilege at the same time, according to Andromeda Security. Static approval logic breaks once access decisions need to reflect runtime risk, not just role and schedule.
Editorial analysis by NHI Mgmt Group, based on content published by Andromeda Security: “How to Automate JIT Access for High Security and Improved Productivity”.
Key questions
Q: What breaks when JIT approvals rely only on role and schedule?
A: Static JIT breaks when it treats identity as stable and predictable.
Q: Why does context-aware JIT reduce security risk more effectively?
A: Context-aware JIT can evaluate whether a request matches the requester’s normal behaviour, device, location, and recent access history before granting privilege.
Q: What are the signs that a JIT programme is not really enforcing least privilege?
A: Common warning signs include rubber-stamped approvals, long approval delays, frequent bypasses, and repeated access requests that look identical regardless of context.
Practitioner guidance
- Replace role-only auto-approval logic Remove static allow rules that approve access solely because a requester belongs to a team or requests during business hours.
- Define the risk signals that trigger review Specify which behavioural changes, repeated requests, or context shifts force a manual review before high-risk access is granted.
- Measure approval bypass pressure Track how often requests are rubber-stamped, delayed, or bypassed because the JIT process slows delivery.
Bottom line: Manual and rule-based JIT reduce exposure only when they can see the current identity context, not just a role or time window.
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This topic was modified 10 months ago by Abdelrahman
This topic was modified 6 days ago by NHI Mgmt Group
Mr NHI reacted
04/12/2025 2:39 am
The JIT model in that article highlights the same issue we see in agent security today. Static permissions and static trust signals break down the moment identities or operational context change. Dynamic JIT works because it reevaluates risk at the moment of use instead of assuming yesterday’s state is still valid.
The same shift is happening with AI agents. Once you have agents invoking tools, calling APIs, or interacting over protocols like MCP or A2A, standing privileges become a liability. You need verification at the point of execution, not just at onboarding. The World Economic Forum calls this out directly in their new agent governance paper, noting that autonomy, authority, and operational context create a different risk surface that traditional IAM can’t handle.
If anyone here is exploring how to handle identity, integrity, and least-privilege enforcement for agents, this overview may help. It outlines how to verify agent identity, capabilities, and domain control using open standards, without introducing friction into workflows:
Mr NHI reacted
06/10/2026 4:37 pm
Static JIT is a governance approximation, not a control boundary: When approval decisions rely on role, title, or request time, they inherit the assumptions of standing privilege. That model can reduce friction, but it cannot tell whether the access request is safe in the current context. The practitioner lesson is that a time-limited grant is not the same thing as a dynamically justified grant.
A few things that frame the scale:
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to the Ultimate Guide to NHIs.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems. Organisations failing to scope AI access properly are 4.5x more likely to experience a security incident, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How should teams balance friction and security in B2C authentication?
A: Use the least friction that still matches the risk of the session or action. Keep ordinary sign-ins simple, then apply adaptive MFA or step-up verification only when device, location, behaviour, or transaction value raises the assurance requirement. This approach protects conversion while still allowing stronger checks where they matter most.
👉 Read our full editorial: AI-powered JIT access exposes the limits of standing privilege