aws-resource-validator-datazone

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks across all categories assessed and does not indicate any malicious intent. The low metadata risk is noted but does not raise significant concerns.

  • No network calls detected
  • No shell execution patterns
  • No obfuscation or credential harvesting
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating no immediate signs 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 details are sparse, indicating potential low activity or newness, but no clear signs 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 (303 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-datazone 
Create a Python-based CLI tool named 'DataZoneChecker' that leverages the 'aws-resource-validator-datazone' package to validate resources within an AWS DataZone environment. This tool should serve as a comprehensive utility for developers and administrators to ensure their AWS DataZone configurations adhere to best practices and standards.

### Features:
1. **Resource Validation**: Users should be able to input details of various AWS DataZone resources (such as environments, domains, projects, etc.) via a YAML file or directly through command-line arguments. The tool will then validate these resources against predefined schemas provided by 'aws-resource-validator-datazone'.
2. **Detailed Reporting**: Upon validation, the tool should generate a detailed report highlighting any discrepancies found during the validation process. This report should include error messages and suggestions for corrections.
3. **Integration with AWS SDK**: The tool should integrate with the AWS SDK for Python (Boto3) to allow users to automatically fetch resource configurations from their AWS DataZone environment and validate them against the schemas.
4. **Customizable Schemas**: Advanced users should have the ability to define custom validation schemas using the 'aws-resource-validator-datazone' package's Pydantic models, allowing for more granular control over validation criteria.
5. **Interactive Mode**: For a more user-friendly experience, include an interactive mode where users can input resource details one at a time and receive immediate feedback on the validity of each resource.
6. **Exportable Results**: Allow users to export the validation results into different formats such as JSON or CSV for further analysis or record-keeping.

### Utilization of 'aws-resource-validator-datazone':
- Use the Pydantic models provided by 'aws-resource-validator-datazone' to define the structure and constraints for various AWS DataZone resources.
- Leverage the package's validation capabilities to enforce these structures and constraints when validating user-provided resource configurations.
- Implement error handling and reporting mechanisms that utilize the error messages and schema descriptions provided by 'aws-resource-validator-datazone' to enhance user feedback.

This project aims to streamline the process of ensuring AWS DataZone resources meet organizational standards, thereby improving overall data governance and security.

💬 Discussion Feed

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