Access Analyzer KMS

Calculates whether a given principal can perform a specified action on a KMS resource based on policy documents and conditions.

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About This Tool

Access Analyzer KMS is a policy evaluation tool that lets security and cloud engineers validate whether a specified principal can perform a chosen KMS action on a given key by cross-checking IAM and KMS resource policies. It helps identify over-privilege and compliance gaps in multi-account environments.
Conceptually, it ingests policy documents, resource ARNs, and the action, then applies the standard policy evaluation logic to compute a yes/no outcome and a justification. The engine does not execute real API calls; it simulates permission checks in a deterministic manner.
Who benefits: developers integrating with cloud keys, security engineers auditing key access, and auditors verifying least-privilege controls. Unique value lies in combining policy parsing, cross-policy aggregation, and exportable results in both human-readable and machine-readable formats for automation.
Core features include input validation, policy normalization, denial-first evaluation, multi-policy reconciliation, and actionable outputs such as recommended mitigations and example denial paths.

How to Use

  1. Provide inputs: principal, action, key ARN, and policy documents.
  2. Choose evaluation scope: identity-based vs resource-based policies.
  3. Run calculation: initiate the policy evaluation to compute a decision.
  4. Review outputs: inspect the decision, matched policies, and justification.
  5. Export results: download or copy the JSON report for automation.
How to use access analyzer kms

Frequently Asked Questions

Find Quick Answers

What inputs are required?
Required inputs include the principal ARN, the KMS key ARN, the action, and the policy documents that govern the principal's permissions. Optional context like region or account IDs can refine evaluation results.
What does the output include?
The tool returns a decision (Allow, Deny, or NotApplicable), the rationale, the policies that contributed, and suggested mitigations or least-privilege adjustments. Outputs are suitable for automation and audits.
How are conditional expressions handled?
Conditions are evaluated using the same semantics as the source policies: matching keys, time, IP, or principal attributes, with Deny policies taking precedence over Allows. Complex conditions may constrain the final outcome.
Is this model cloud-provider specific?
The tool models AWS IAM and KMS policy semantics and is most accurate for AWS-like environments. It can be adapted to similar cloud providers with equivalent policy constructs, but differences may affect results.

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