IAM and PAM were designed around authentication and privileged session control, not the full entitlement graph created by cloud policies. They can confirm who logged in and protect elevated sessions, but they do not reliably show what a role can reach after inheritance, trust relationships, and group-based access are resolved. That is why over-permissioned identities remain hidden.
Why This Matters for Security Teams
IAM and PAM are necessary, but they are not enough when cloud access is assembled from roles, resource policies, trust relationships, group membership, and inherited permissions. The gap is not in authentication alone; it is in entitlement resolution across environments that change faster than manual reviews can keep up. OWASP’s OWASP Non-Human Identity Top 10 treats this as a core NHI failure mode, and NHIMG research shows how often teams underestimate it in practice.
That underestimation matters because hidden reach is where over-permissioning becomes exploitable. A role that appears narrow in an IAM console may still inherit broad data-plane access through a trust policy, or gain lateral movement through a service-linked role, a nested group, or an attached policy that was never revisited after deployment. The result is a false sense of control: teams think they have bounded access, while the actual permission graph keeps expanding. In the Ultimate Guide to NHIs, NHIMG highlights that multi-cloud and hybrid sprawl routinely outpace access governance processes. In practice, many security teams encounter permission drift only after a sensitive resource has already been reachable for weeks or months, rather than through intentional review.
How It Works in Practice
Cloud permission gaps emerge because the effective privilege of an identity is the sum of multiple layers, not the label attached to the account. IAM tells you what a principal is assigned directly. PAM protects an elevated session once someone is already privileged. Neither one fully reconstructs the real entitlement graph that cloud platforms use at request time.
To close the gap, security teams need to evaluate access as a graph problem and a runtime problem. That usually means resolving:
- Direct role assignments and attached policies
- Inherited permissions from parent groups, accounts, or management scopes
- Trust relationships between services, accounts, and workloads
- Resource-based policies that override or extend identity-based rules
- Cross-account and cross-project access paths
Current guidance suggests combining continuous entitlement analysis with policy-as-code, because static reviews age quickly in cloud environments. NIST’s Zero Trust Architecture is relevant here because it shifts the question from “is this identity authenticated?” to “should this request be allowed right now, in this context?” For non-human identities, the same logic applies to secrets and workload access. NHIMG’s reporting on the 2024 Non-Human Identity Security Report shows that many organisations still lag in dynamic, ephemeral access models, which is exactly where hidden cloud permissions become visible.
Operationally, teams should verify effective permissions after inheritance is resolved, enforce least privilege at the resource boundary, and automate alerting for policy changes that expand reach. These controls tend to break down when multiple cloud accounts, legacy role chaining, and third-party integrations all delegate access through different policy engines, because no single console view shows the full path.
Common Variations and Edge Cases
Tighter entitlement control often increases operational overhead, requiring organisations to balance visibility against the cost of maintaining accurate policy models. That tradeoff becomes sharper in mature cloud estates, where central security teams do not own every role, and platform teams need enough freedom to ship changes quickly.
There is no universal standard for this yet, but best practice is evolving toward continuous discovery plus just-in-time enforcement. Some environments can tolerate periodic entitlement review if the cloud footprint is small and stable. Others, especially those with Kubernetes, multi-account AWS, federated SaaS, or CI/CD automation, need near-real-time analysis because permissions are created and discarded too quickly for manual approval to keep up.
Two edge cases deserve special attention. First, “read-only” roles are often not harmless: metadata access, secrets discovery, and control-plane visibility can still support lateral movement. Second, PAM does not solve machine-to-machine exposure, because the risky path is often not a human session at all. NHIMG’s Snowflake breach and 230M AWS environment compromise research both show how quickly hidden access paths become real incident paths when credentials, trust, and entitlement drift are left ungoverned.
In short, IAM and PAM are controls for known identities and known privilege states, while cloud risk increasingly lives in the unknown paths between them.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 | Effective privilege gaps often come from unmanaged credential and access drift. |
| NIST CSF 2.0 | PR.AC-4 | This control maps to managing access permissions and enforcing least privilege. |
| NIST AI RMF | AI risk management applies when autonomous systems create dynamic access paths. |
Verify effective cloud permissions continuously and remove excess access at the resource boundary.
