aws-resource-validator-redshift-serverless

v2.0.3 safe
4.0
Medium Risk

Pydantic v2 models for AWS redshift_serverless, shipped as a PEP 420 namespace extension of aws-resource-validator.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network, shell, or credential risks. The metadata risk is slightly elevated due to sparse author information, but this alone is insufficient to conclude malicious activity.

  • No network calls detected
  • No shell execution patterns
  • Sparse author metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no immediate risk of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's information is sparse and may indicate a less reputable source, but there are no clear signs of malicious intent.

📦 Package Quality Overall: Low (3.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (336 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 75 commits in CoreOxide/aws_resource_validator
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository CoreOxide/aws_resource_validator appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aws-resource-validator-redshift-serverless 
Create a utility application named 'RedshiftServerlessValidator' using Python that leverages the 'aws-resource-validator-redshift-serverless' package to validate Redshift Serverless resources. This application will serve as a tool for developers and system administrators to ensure their AWS Redshift Serverless configurations adhere to best practices and compliance standards. Here’s a detailed breakdown of the application’s requirements and functionalities:

1. **Setup**: Ensure your development environment has Python 3.8+ installed, along with the required dependencies including boto3 for AWS SDK and pydantic for model validation.
2. **Authentication**: Implement AWS IAM role or access keys for authenticating the application with AWS services. The application should securely handle these credentials.
3. **Resource Validation**: Utilize the 'aws-resource-validator-redshift-serverless' package to define and validate Redshift Serverless resources such as workspaces, usage quotas, and security groups against predefined schemas. The validation process should check for common misconfigurations, such as overly permissive permissions, incorrect settings, and unsupported parameters.
4. **Interactive CLI**: Develop a command-line interface (CLI) that allows users to input resource details and receive validation results immediately. Users should be able to specify which type of Redshift Serverless resource they want to validate (e.g., workspace, usage quota).
5. **Detailed Reports**: Upon validation, generate comprehensive reports detailing any issues found, suggestions for improvement, and a summary of the overall health of the specified resources. These reports should be both human-readable and machine-readable formats like JSON or CSV.
6. **Custom Rules**: Allow users to add custom validation rules through configuration files. This feature enables organizations to enforce specific policies tailored to their needs beyond the default validations provided by the package.
7. **Integration Testing**: Write unit tests and integration tests to ensure the application functions correctly under various scenarios, including edge cases and large datasets.
8. **Documentation**: Provide clear documentation on how to install, configure, and use the 'RedshiftServerlessValidator'. Include examples and best practices for setting up Redshift Serverless resources effectively.

By following these steps and utilizing the 'aws-resource-validator-redshift-serverless' package, you’ll create a robust tool that enhances security, compliance, and efficiency when managing AWS Redshift Serverless environments.

💬 Discussion Feed

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