Identity and Access Management Access Analyzer helps you to set, verify, and refine your IAM policies by providing a suite of capabilities. Its features include findings for external and unused access, basic and custom policy checks for validating policies, and policy generation to generate fine-grained policies. To start using IAM Access Analyzer to identify external or unused access, you first need to create an analyzer.
External access analyzers help identify potential risks of accessing resources by enabling you to identify any resource policies that grant access to an external principal. It does this by using logic-based reasoning to analyze resource-based policies in your Amazon Web Services environment. An external principal can be another Amazon Web Services account, a root user, an IAM user or role, a federated user, an Amazon Web Services service, or an anonymous user. You can also use IAM Access Analyzer to preview public and cross-account access to your resources before deploying permissions changes.
Unused access analyzers help identify potential identity access risks by enabling you to identify unused IAM roles, unused access keys, unused console passwords, and IAM principals with unused service and action-level permissions.
Beyond findings, IAM Access Analyzer provides basic and custom policy checks to validate IAM policies before deploying permissions changes. You can use policy generation to refine permissions by attaching a policy generated using access activity logged in CloudTrail logs.
This guide describes the IAM Access Analyzer operations that you can call programmatically. For general information about IAM Access Analyzer, see Identity and Access Management Access Analyzer in the IAM User Guide.
tags: - name: Amazon Web Services Redshift Data paths: /: POST: summary: Amazon Web Services Listtables description: 'List the tables in a database. If neither SchemaPattern nor TablePattern are specified, then all tables in the database are returned. A token is returned to page through the table list. Depending on the authorization method, use one of the following combinations of request parameters: Secrets Manager - when connecting to a cluster, provide the secret-arn of a secret stored in Secrets Manager which has username and password. The specified secret contains credentials to connect to the database you specify. When you are connecting to a cluster, you also supply the database name, If you provide a cluster identifier (dbClusterIdentifier), it must match the cluster identifier stored in the secret. When you are connecting to a serverless workgroup, you also supply the database name. Temporary credentials - when connecting to your data warehouse, choose one of the following options: When connecting to a serverless workgroup, specify the workgroup name and database name. The database user name is derived from the IAM identity. For example, arn:iam::123456789012:user:foo has the database user name IAM:foo. Also, permission to call the redshift-serverless:GetCredentials operation is required. When connecting to a cluster as an IAM identity, specify the cluster identifier and the database name. The database user name is derived from the IAM identity. For example, arn:iam::123456789012:user:foo has the database user name IAM:foo. Also, permission to call the redshift:GetClusterCredentialsWithIAM operation is required. When connecting to a cluster as a database user, specify the cluster identifier, the database name, and the database user name. Also, permission to call the redshift:GetClusterCredentials operation is required. For more information about the Amazon Redshift Data API and CLI usage examples, see Using the Amazon Redshift Data API in the Amazon Redshift Management Guide. ' operationId: amazonWebServicesListTables tags: - Amazon Web Services Redshift Data