AWServices IAM AI-AWS IAM policy generator tool

Example

A user requires a policy to grant Lambda function access to a DynamoDB table, but only to read specific items based on a condition (e.g., filtering by a specific attribute value). AWServices IAM AI can create a custom policy that uses 'Condition' elements in JSON to apply fine-grained controls to the DynamoDB actions.

Scenario

Developers working with serverless applications often need to grant AWS Lambda limited access to data resources, such as DynamoDB tables or S3 buckets. AWServices IAM AI helps by generating policies that allow the function to read from the DynamoDB table only when certain conditions are met, reducing the risk of over-permissioning.

Example

A user unfamiliar with IAM policy structure asks about the difference between 'Action' and 'Resource' in IAM policy JSON. AWServices IAM AI explains that 'Action' defines what API operations (like 's3:GetObject') can be performed, while 'Resource' specifies which AWS resources (e.g., an S3 bucket) those actions apply to.

Scenario

New AWS users often struggle with understanding the structure of IAM policies, which can lead to misconfigurations. AWServices IAM AI can clarify the roles of different policy components, reducing the likelihood of errors and helping users follow best practices.

Example

A user requests a policy to allow 'developers' access to 'manage' EC2 resources but doesn’t specify further details. Based on best practices, AWServices IAM AI generates a policy with only essential EC2 permissions (e.g., starting, stopping, and describing instances), but with restricted access to sensitive operations like changing instance roles.

Scenario

When users make vague requests about permissions, AWServices IAM AI can apply industry knowledge to recommend policies aligned with the principle of least privilege. For example, when granting developer access, it may prioritize operational tasks while preventing more sensitive administrative functions.