aws-resource-validator-mwaa

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network, shell, obfuscation, and credential handling. However, the metadata risk score is elevated due to incomplete author details and a single package from the same author, suggesting potential novice behavior or caution is needed.

  • Incomplete author metadata
  • Single package from the author
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 direct system command executions.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's details are incomplete and the author has only one package, which could indicate a less experienced or potentially suspicious user.

📦 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 (291 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 
Create a Python-based utility named 'MWAAValidator' that leverages the 'aws-resource-validator-mwaa' package to validate Amazon MWAA (Managed Workflows for Apache Airflow) resources against Pydantic v2 models. This utility should serve as a tool for developers and DevOps engineers to ensure their MWAA environments and workflows comply with specified standards and configurations.

The application should include the following core functionalities:
1. **Resource Validation**: Implement functions to validate different MWAA resources such as Environments, DAGs, and Connections using Pydantic models provided by 'aws-resource-validator-mwaa'.
2. **Configuration Compliance Check**: Allow users to define a configuration file (YAML or JSON format) that outlines expected resource properties. The utility should then compare these definitions against actual MWAA resources to check for compliance.
3. **Reporting**: Provide a reporting feature that generates a detailed report on the validation process, highlighting any discrepancies between the defined configurations and actual resources.
4. **Interactive CLI**: Develop a command-line interface (CLI) that allows users to easily run validations, specify configuration files, and view reports without needing to write scripts.
5. **Integration with CI/CD Pipelines**: Enable the utility to be integrated into CI/CD pipelines, ensuring that MWAA resources adhere to the defined standards before deployment.

How 'aws-resource-validator-mwaa' is utilized:
- Use the Pydantic models from 'aws-resource-validator-mwaa' to define the structure and constraints of MWAA resources.
- Validate MWAA resources by instantiating these models with actual resource data and checking for validation errors.
- Utilize the package's namespace extension capabilities to streamline the inclusion of additional models or updates to the validation logic.

Your task is to design and implement the 'MWAAValidator' utility, ensuring it is modular, extensible, and well-documented. Additionally, provide examples and documentation on how to integrate this utility into existing MWAA workflows and CI/CD pipelines.

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