feat(query): lambda function without dead letter queue query implemented for Terraform/aws

[cx-ricardo-jesus]

Reason for Proposed Changes

• Currently we have no support in Terraform when there's a "Lambda Function Without Dead Letter Queue", which we currently have for the CloudFormation platform.

Proposed Changes

• To develop this query for Terraform platform, I used a similar approach as the one used for the CloudFormation query.
• This query only has one policy, that uses a helper function called is_dead_letter_queue_undefined_or_empty used to check if the resource aws_lambda_function does not have the field dead_letter_config field defined or when it's defined but the field target_arn inside it, has a empty value(empty string).
• Comparing with the CloudFormation query implementation, this one does not return a positive result is the target_arn field is defined but with nothing within, not even a empty string, because having this field defined with nothing is not valid for this resource on Terraform since it is a field that is required when the field dead_letter_config is defined.
• Instead of that, I made a verification that check's the cases when the field target_arn is defined with a empty string.
• Added one negative sample that has the field dead_letter_config.target_arn correctly defined.
• Added two positive samples, one of them returns a positive result because the field dead_letter_config field is not defined and the other one returns a positive result because the field dead_letter_config.target_arn is defined with a empty string.

I submit this contribution under the Apache-2.0 license.

[github-actions]

KICS version: v2.1.11

Category Results CRITICAL 0 HIGH 0 MEDIUM 0 LOW 0 INFO 0 TRACE 0 TOTAL 0	Metric Values Files scanned 1 Files parsed 1 Files failed to scan 0 Total executed queries 47 Queries failed to execute 0 Execution time 0

[cx-eduardo-semanas]

LGTM

[gitguardian]

⚠️ GitGuardian has uncovered 2 secrets following the scan of your pull request.

Please consider investigating the findings and remediating the incidents. Failure to do so may lead to compromising the associated services or software components.

🔎 Detected hardcoded secrets in your pull request

GitGuardian id	GitGuardian status	Secret	Commit	Filename
4266022	Triggered	Generic Password	dcf0cee	assets/queries/cloudFormation/aws/amplify_app_basic_auth_config_password_exposed/test/negative7.yaml	View secret
9419039	Triggered	Username Password	dcf0cee	assets/queries/cloudFormation/aws/amplify_branch_basic_auth_config_password_exposed/test/positive6.json	View secret

🛠 Guidelines to remediate hardcoded secrets

1. Understand the implications of revoking this secret by investigating where it is used in your code.
2. Replace and store your secrets safely. Learn here the best practices.
3. Revoke and rotate these secrets.
4. If possible, rewrite git history. Rewriting git history is not a trivial act. You might completely break other contributing developers' workflow and you risk accidentally deleting legitimate data.

To avoid such incidents in the future consider

• following these best practices for managing and storing secrets including API keys and other credentials
• install secret detection on pre-commit to catch secret before it leaves your machine and ease remediation.

---

^{🦉 GitGuardian detects secrets in your source code to help developers and security teams secure the modern development process. You are seeing this because you or someone else with access to this repository has authorized GitGuardian to scan your pull request.}