Resolving ‘Getting the Policy Failed Legacy Parsing When Creating an AWS IAM Policy’ Errors

When creating an AWS IAM policy, encountering the error “policy failed legacy parsing” indicates that the policy document does not conform to the expected JSON structure or syntax. This error is significant because it prevents the policy from being created or applied, which can hinder the management of permissions and access controls within AWS. Ensuring correct policy syntax is crucial for maintaining secure and functional IAM policies.

Understanding the Error

When you encounter the error “the policy failed legacy parsing” while creating an AWS IAM policy, it means that the policy document you provided does not conform to the expected JSON structure or contains syntax errors that prevent it from being parsed correctly by AWS.

Common Causes:

1. Incorrect JSON Structure:

   • Missing or Extra Commas: JSON syntax errors like missing or extra commas can cause this error.
   • Incorrect Brackets: Mismatched or misplaced curly braces {} or square brackets [].

2. Improper Policy Elements:

   • Version Element: The Version element must be the first key in the policy document.
   • Statement Element: The Statement element should be an array, even if it contains only one statement.

3. Invalid Actions or Resources:

   • Typographical Errors: Misspelled actions or resource ARNs.
   • Unsupported Actions: Using actions that are not supported by the service.

4. Use of Pseudo Parameters:

   • Incorrect Syntax: Using incorrect syntax for AWS pseudo parameters like ${AWS::AccountId} instead of #{AWS::AccountId}.

Scenarios:

1. Terraform or CloudFormation Deployments:

   • Policies defined in Terraform or CloudFormation templates might fail due to syntax errors or improper formatting.

2. Manual Policy Creation via AWS CLI or Console:

   • Manually creating or editing policies in the AWS Management Console or using the AWS CLI can lead to errors if the JSON is not correctly formatted.

3. Serverless Framework Deployments:

   • Deploying serverless applications with IAM roles and policies might encounter this error if the policy document contains legacy parsing issues.

Ensuring the policy document adheres to the correct JSON structure and syntax is crucial to avoid this error. Double-checking the policy elements and using tools like JSON validators can help identify and fix these issues.

Common Mistakes Leading to the Error

Here are common mistakes that lead to the “policy failed legacy parsing” error when creating an AWS IAM policy, along with examples of incorrect policy documents:

1. Incorrect JSON Syntax:

   • Mistake: Missing commas, brackets, or quotes.
   • Example:

     {
       "Version": "2012-10-17"
       "Statement": [
         {
           "Effect": "Allow",
           "Action": "s3:ListBucket",
           "Resource": "arn:aws:s3:::example_bucket"
         }
       ]
     }
     

2. Invalid Action Names:

   • Mistake: Using incorrect or non-existent action names.
   • Example:

     {
       "Version": "2012-10-17",
       "Statement": [
         {
           "Effect": "Allow",
           "Action": "s3:ListBuckets",  // Incorrect action name
           "Resource": "arn:aws:s3:::example_bucket"
         }
       ]
     }
     

3. Incorrect ARN Format:

   • Mistake: Using an incorrect Amazon Resource Name (ARN) format.
   • Example:

     {
       "Version": "2012-10-17",
       "Statement": [
         {
           "Effect": "Allow",
           "Action": "s3:ListBucket",
           "Resource": "arn:aws:s3:example_bucket"  // Missing colons and bucket name
         }
       ]
     }
     

4. Using NotAction with Allow Effect:

   • Mistake: Combining NotAction with Effect: Allow.
   • Example:

     {
       "Version": "2012-10-17",
       "Statement": [
         {
           "Effect": "Allow",
           "NotAction": "iam:*",
           "Resource": "*"
         }
       ]
     }
     

5. Missing Required Elements:

   • Mistake: Omitting required elements like Effect, Action, or Resource.
   • Example:

     {
       "Version": "2012-10-17",
       "Statement": [
         {
           "Action": "s3:ListBucket",
           "Resource": "arn:aws:s3:::example_bucket"
         }
       ]
     }
     

6. Invalid Condition Keys or Values:

   • Mistake: Using incorrect condition keys or values.
   • Example:

     {
       "Version": "2012-10-17",
       "Statement": [
         {
           "Effect": "Allow",
           "Action": "s3:ListBucket",
           "Resource": "arn:aws:s3:::example_bucket",
           "Condition": {
             "StringEquals": {
               "aws:username": "example_user"  // Incorrect condition key
             }
           }
         }
       ]
     }
     

These mistakes can cause parsing errors and prevent the policy from being applied correctly. Always validate your JSON syntax and ensure all elements are correctly specified.

Troubleshooting Steps

1. Check JSON Syntax:

   • Ensure the policy document is valid JSON.
   • Use a JSON validator tool to identify syntax errors.

2. Verify Policy Structure:

   • Confirm the Version field is correct (e.g., "Version": "2012-10-17").
   • Ensure Statement is an array, even if it contains only one statement.

3. Validate Actions and Resources:

   • Check that all actions and resources are correctly specified.
   • Ensure there are no typos in action names or resource ARNs.

4. Check for Unsupported Characters:

   • Remove any unsupported characters or formatting issues.
   • Avoid using special characters that might not be parsed correctly.

5. Review Policy Length:

   • Ensure the policy does not exceed the size limits set by AWS.

6. Use AWS Policy Simulator:

   • Test the policy using the AWS IAM Policy Simulator to identify issues.

7. Check for Duplicate Elements:

   • Remove any duplicate elements or SID values in the policy.

8. Correct Principal Specification:

   • Ensure the Principal field is correctly specified, especially in resource-based policies.

9. Review AWS Documentation:

   • Refer to AWS documentation for specific service requirements and examples.

10. Test with AWS CLI:

    • Deploy the policy using AWS CLI to check for any differences in behavior.

These steps should help you identify and correct issues causing the “policy failed legacy parsing” error.

Best Practices

To avoid the “policy failed legacy parsing” error when creating an AWS IAM policy, follow these best practices:

1. Correct JSON Syntax: Ensure your policy document is valid JSON. Use tools like JSONLint to validate the syntax.
2. Proper Version Element: Include the Version element outside the Statement element. Use "Version": "2012-10-17" for most policies.
3. Array for Statements: The Statement element should be an array, even if it contains only one statement.
4. Action and Resource Elements: Ensure Action and Resource elements are correctly specified. Use wildcards carefully and validate ARNs.
5. Indentation and Formatting: Maintain consistent indentation and formatting to improve readability and reduce errors.

Proper syntax and structure are crucial as they ensure the policy is interpreted correctly by AWS, preventing errors and ensuring the intended permissions are applied securely and effectively.

Preventing ‘Policy Failed Legacy Parsing’ Error in AWS IAM

When creating an AWS IAM policy, ensure you follow best practices to avoid the 'policy failed legacy parsing' error. This error occurs due to incorrect syntax, structure, or formatting in the policy document. To prevent this issue, carefully review and validate your policy before deploying it.

Best Practices for Validating AWS IAM Policies

1. Verify that your policy document is valid JSON using tools like JSONLint. Ensure the <code>Version</code> element is correctly specified outside the <code>Statement</code> element, typically as <code>"Version": "2012-10-17"</code>. The <code>Statement</code> element should be an array, even if it contains only one statement.
2. Ensure that all action and resource elements are correctly specified. Use wildcards carefully and validate ARNs to avoid typos or formatting issues. Maintain consistent indentation and formatting throughout the policy document for improved readability and reduced errors.
3. Check for duplicate elements or SID values in the policy, as these can cause parsing errors. Review AWS documentation for specific service requirements and examples to ensure your policy meets all necessary conditions.

Testing Your Policy

Finally, test your policy using the AWS IAM Policy Simulator to identify any issues before deploying it. Deploying a policy with errors can lead to unintended consequences, including security vulnerabilities or access control issues.

By following these best practices and carefully reviewing your policy document, you can avoid the 'policy failed legacy parsing' error and ensure that your AWS IAM policies are correctly interpreted and applied securely and effectively.