aws-resource-validator-mwaa-serverless

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no direct signs of malicious intent based on current analysis, but the metadata risk score due to the author's account status raises concern. Further investigation into the author's background and the package's usage history is recommended.

  • Low risk scores across all technical indicators
  • Metadata risk due to author's account status
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity without further context.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands, reducing potential risks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has a new or inactive account and lacks a proper name, raising some suspicion but not conclusive evidence of malice.

📦 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 (324 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-mwaa-serverless 
Create a Python-based command-line tool named 'MWAAValidatorCLI' that leverages the 'aws-resource-validator-mwaa-serverless' package to validate Amazon MWAA (Managed Workflows for Apache Airflow) serverless configurations. This tool will help developers and operators ensure their MWAA environments are correctly configured according to best practices and AWS guidelines.

### Project Goals:
- **Validation**: Validate MWAA serverless environment configurations against predefined schemas using Pydantic models provided by the 'aws-resource-validator-mwaa-serverless' package.
- **Reporting**: Provide a detailed report of validation results, highlighting any issues found in the configuration.
- **Integration**: Allow for easy integration with existing CI/CD pipelines, such as GitHub Actions or GitLab CI.
- **User-Friendly**: Ensure the CLI is intuitive and easy to use, with clear error messages and usage instructions.

### Features:
1. **Configuration Validation**: Automatically validate MWAA serverless configurations against Pydantic models.
2. **Custom Rules**: Allow users to define custom validation rules or exceptions through a configuration file.
3. **Output Formats**: Support multiple output formats for reports, including plain text, JSON, and HTML.
4. **Interactive Mode**: Offer an interactive mode where users can input configurations directly from the command line for immediate validation feedback.
5. **Version Control**: Check if the MWAA serverless environment configuration matches the latest version of the Pydantic models provided by 'aws-resource-validator-mwaa-serverless'.
6. **Help and Documentation**: Comprehensive help documentation and examples for common use cases.

### Utilizing 'aws-resource-validator-mwaa-serverless':
- Import the necessary Pydantic models from the 'aws-resource-validator-mwaa-serverless' package to define the structure and constraints of valid MWAA serverless configurations.
- Use these models to validate user-provided configurations, catching any discrepancies early in the development process.
- Leverage the package's namespace extension capabilities to easily integrate additional validation rules or extend functionality without modifying the core models.
- Consider contributing back to the 'aws-resource-validator-mwaa-serverless' community with any custom validation rules or enhancements developed during the project.

💬 Discussion Feed

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