aws-resource-validator-cleanrooms

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risk indicators with no network calls, shell executions, or obfuscations detected. The metadata risk is slightly elevated due to sparse author information.

  • No network calls
  • Sparse author information
Per-check LLM notes
  • Network: No network calls detected, which is normal for packages that do not require internet access.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
  • Metadata: The author's information is sparse, indicating potential unreliability, but no clear 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 (309 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-cleanrooms 
Create a Python-based CLI tool named 'Cleanroom Validator' that leverages the 'aws-resource-validator-cleanrooms' package to validate AWS Cleanrooms configurations against predefined schemas. This tool will help developers and DevOps engineers ensure their AWS Cleanrooms resources adhere to best practices and company standards before deployment. The application should support the following features:

1. **Configuration Loading**: Allow users to load AWS Cleanrooms configurations from a YAML file or JSON input.
2. **Validation Against Schema**: Use the Pydantic models provided by 'aws-resource-validator-cleanrooms' to validate the loaded configurations against specific AWS Cleanrooms schemas.
3. **Detailed Validation Reports**: Generate comprehensive reports detailing any validation errors or warnings found during the schema validation process.
4. **Interactive Mode**: Implement an interactive mode where users can input configurations directly into the CLI and receive real-time validation feedback.
5. **Customizable Schemas**: Enable users to specify which schemas they want to validate against, allowing for flexibility based on different use cases and requirements.
6. **Error Handling**: Ensure robust error handling, providing clear and user-friendly error messages when issues are encountered.
7. **Integration with CI/CD Pipelines**: Facilitate easy integration with common CI/CD tools like GitHub Actions or Jenkins, enabling automated validation of AWS Cleanrooms configurations as part of the pipeline.
8. **Logging and Auditing**: Include logging capabilities to track validation activities and maintain an audit trail of all validation runs.

The 'aws-resource-validator-cleanrooms' package plays a crucial role in this project by providing the necessary Pydantic models that define the structure and rules for valid AWS Cleanrooms configurations. These models will be used to validate the user-provided configurations, ensuring they meet the required standards and formats before being deployed in production environments.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!