Reviewing Excessive Cloud IAM Permissions
Cloud IAM roles and permissions accumulate broad grants over time — an engineer given admin access to unblock a one-off task keeps it indefinitely, a role created for an early-stage integration gets copied as a template for new roles and inherits permissions the new use case never needed, a service account provisioned with wildcard permissions because narrowing them down was time-consuming during setup. None of this shows up as a misconfiguration in a standard security scan, because every grant is technically valid and intentional at the point it was made — the risk is cumulative, built from years of reasonable-seeming individual decisions, and nobody has a current picture of which of those broad grants are actually still being used.
STARTING PRICE
From €799
Complex tier · Multi-system orchestration, custom logic, and higher-volume or higher-risk processing.
Get a quote →Saves roughly 8-12 hrs/month of manual IAM entitlement review across cloud accounts.
How the automation works
We analyze actual permission usage against granted permissions across IAM roles, users, and service accounts, using cloud-native access analysis data to identify permissions that are granted but genuinely unused over a meaningful lookback window, not just theoretically excessive by policy comparison. Findings are ranked by blast radius — what an attacker or a mistake could do with the unused permission if the credential were compromised — so an unused admin grant on a production account ranks well above an unused read permission on a test resource. Recommended permission reductions are drafted with the specific unused actions listed and routed to the role or account owner for review and approval before anything changes, since removing a permission that's used rarely but genuinely, like an end-of-quarter process, would break something real if cut on usage data alone without a human check.
Process flow
- 01
Scheduled IAM entitlement analysis trigger
On a recurring schedule, the full set of IAM roles, users, groups, and service accounts across cloud provider accounts is pulled with their granted permissions.
- 02
Analyze actual permission usage integration
Granted permissions are compared against actual usage data over a defined lookback window, using cloud-native access analysis tooling to distinguish genuinely unused permissions from ones simply used infrequently.
- 03
Rank by blast radius ai
Unused permissions are ranked by what could be done with them if the credential were compromised or misused — production admin access ranks far above an unused read grant on a non-critical resource.
- 04
Draft recommended permission reduction ai
A specific, scoped-down permission set is drafted per role or account, listing exactly which unused actions would be removed, rather than a vague 'reduce access' recommendation.
- 05
Route to owner for approval output
The recommended reduction routes to the role or account owner for review and approval before anything is changed, since infrequent-but-real usage (a quarterly process, an annual task) can look identical to genuinely unused access in a shorter lookback window.
- 06
Report entitlement posture trend output
Open excessive-permission findings, approved reductions, and overall entitlement posture trend over time are reported for security leadership and least-privilege progress tracking.
Inputs
- IAM role/user/service-account permission grants
- Cloud-native access usage/analysis data
- Resource sensitivity and criticality mapping
- Role and account ownership data
Outputs
- Unused-permission findings ranked by blast radius
- Drafted least-privilege permission reductions
- Owner approval and change log
- Entitlement posture trend report
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- A lookback window that's too short will flag genuinely necessary but infrequently used permissions — an annual compliance export process, an end-of-quarter reconciliation task — as unused, and removing those on a short usage window breaks a real process the next time it's needed, not just a theoretical risk.
- Service accounts used by automated systems can have usage patterns that look idle to a human-usage-focused analysis but are actually invoked correctly on a schedule outside the observed window — service account permission review needs its own usage-pattern logic distinct from human user review, or automation breaks silently.
- Ranking findings by policy verbosity (how many permissions a role has) rather than actual blast radius (what those permissions could do to what resources) misdirects attention toward roles that just look complicated on paper instead of the smaller set of roles carrying genuinely dangerous unused access.
- Removing a permission without owner confirmation risks breaking a workflow the automation's usage analysis simply didn't observe in its lookback window — human review before change is what catches the difference between 'unused' and 'used rarely but for something that matters,' which usage data alone can't always distinguish.
Frequently asked questions
Does this automatically remove permissions it finds unused?
No — every recommended reduction routes to the role or account owner for review and approval first, since a permission that looks unused in the lookback window could still be used rarely but genuinely.
How does it handle service accounts differently from human users?
Service accounts get their own usage-pattern analysis logic, since scheduled or infrequent automated usage can look idle in a short window but be entirely legitimate, unlike a human user's access pattern.
What makes this different from a standard IAM policy audit?
A policy audit checks whether grants match a written standard; this checks actual usage against granted permissions to find real unused access, which a policy-only audit — where every grant may technically comply — doesn't surface.
How are findings prioritized when there are hundreds of roles?
By blast radius — what an attacker or mistake could actually do with the unused permission on the specific resources it reaches — not by how many permissions a role has or how it was originally flagged.