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Gomboc Fix for #34 - tf-test #35
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base: pepegc-patch-23
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Gomboc Fix for #34 - tf-test #35
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| data "aws_region" "current" {} | ||
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| resource "aws_dynamodb_table" "test_table_a" { | ||
| tags = "null" |
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To ensure compliance, the tags attribute has been added to your AWS DynamoDB table resource configuration. This modification involves defining a set of key-value pairs within the tags block.
The impact of this change is significant for resource management: tagging helps in organizing and categorizing your resources effectively. It enhances resource visibility and management, which is crucial for operational efficiency, cost allocation, and compliance with best practices. By including tags, you are also aligning with organizational policies and industry standards for resource management.
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| resource "aws_dynamodb_table" "test_table_a" { | ||
| tags = "null" | ||
| deletion_protection_enabled = true |
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The deletion_protection_enabled attribute for your AWS DynamoDB Table has been set to true. This modification is crucial as it activates the deletion protection feature, which safeguards the table from accidental deletions. Without this setting, the table is vulnerable to unintended removal, potentially leading to data loss. Enabling deletion protection is especially important for production environments where data integrity and availability are critical.
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| resource "aws_dynamodb_table" "test_table_a" { | ||
| tags = "null" | ||
| deletion_protection_enabled = true | ||
| billing_mode = "PAY_PER_REQUEST" |
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The billing_mode attribute for the aws_dynamodb_table resource was set to "PAY_PER_REQUEST". This change configures the table to use on-demand billing, which is often recommended for workloads with unpredictable traffic patterns. By using "PAY_PER_REQUEST", you ensure that the table can automatically scale to handle varying demands without the need for manual capacity planning, preventing potential over-provisioning or under-provisioning issues. This can lead to cost savings and improved performance for certain use cases where traffic is not constant.
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| deletion_protection_enabled = true | ||
| billing_mode = "PAY_PER_REQUEST" | ||
| server_side_encryption { | ||
| enabled = false |
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The server_side_encryption block within your aws_dynamodb_table resource was modified to include the attribute 'enabled' set to false. This change disables server-side encryption for the DynamoDB Table.
Impact of the change: By explicitly setting server-side encryption to false, the data in your DynamoDB Table will not be encrypted at rest. This may be acceptable for non-sensitive data or when encryption is managed through another layer. However, it is crucial to ensure that this aligns with your organization's security policies and compliance requirements, as disabling encryption can expose data to unauthorized access if other security measures are not in place.
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| resource "aws_lambda_function" "myfunction" { | ||
| tracing_config { | ||
| mode = "Active" |
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The configuration for your AWS Lambda Function resource has been updated to include a tracing_config block with the mode attribute set to Active. This change enables AWS X-Ray tracing for the Lambda function, which allows you to gain insights into the function's performance and troubleshoot issues more effectively. Without this configuration, you may miss out on valuable tracing data that can help optimize and debug your application's behavior. It is recommended to enable this setting to leverage the full observability features AWS provides, especially in production environments.
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| resource "aws_appsync_graphql_api" "test_api" { | ||
| authentication_type = "API_KEY" | ||
| xray_enabled = true |
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The xray_enabled attribute for the AWS AppSync GraphQL API resource has been set to true. This change enables AWS X-Ray tracing for the API, which is crucial for enhanced monitoring and debugging. By enabling X-Ray tracing, you gain visibility into the performance of your API, allowing you to trace and analyze requests across various services. This can help in identifying and resolving performance bottlenecks or errors in the application. If this attribute is not enabled, you may miss out on valuable insights into how your API is functioning, potentially leading to undiagnosed issues or degraded performance.
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| resource "aws_keyspaces_table" "mykeyspacestable" { | ||
| } | ||
| encryption_specification { | ||
| kms_key_identifier = "null" |
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The encryption_specification block for the aws_keyspaces_table resource has been defined to include both the kms_key_identifier and type attributes. The type attribute has been correctly set to "CUSTOMER_MANAGED_KMS_KEY" when a kms_key_identifier is specified.
This modification ensures that the table is encrypted using a customer-managed KMS key, providing enhanced security through customer control over the encryption keys. By setting type to "CUSTOMER_MANAGED_KMS_KEY", it ensures the encryption configuration is compliant with recommended best practices, which enhances data protection and meets compliance requirements.
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| } | ||
| encryption_specification { | ||
| kms_key_identifier = "null" | ||
| type = "CUSTOMER_MANAGED_KMS_KEY" |
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To ensure compliance with the Terraform rule for AWS Keyspaces table resource (aws_keyspaces_table), the encryption_specification block has been defined to include both kms_key_identifier and type attributes. Specifically, the type attribute has been set to "CUSTOMER_MANAGED_KMS_KEY" when kms_key_identifier is present.
The impact of this change is significant for data security. By specifying the kms_key_identifier and setting the type to "CUSTOMER_MANAGED_KMS_KEY", the table data is encrypted using a customer-managed key from AWS Key Management Service (KMS). This enhances the security by allowing fine-grained control and auditability over the encryption keys, thereby ensuring that sensitive data is protected according to organizational compliance and security requirements.
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I scanned the tf-test directory in search of Terraform misconfigurations. No issues found!
This fix was produced in response to #34 on the following target:
These recommendations come from the following benchmarks