aws-resource-validator-dataexchange

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package presents minimal risks based on the analysis notes provided. It does not engage in any network calls, shell executions, or obfuscations that could indicate malicious intent.

  • No network calls detected.
  • Incomplete author information.
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of unauthorized access or data theft.
  • Metadata: The author's information is incomplete, indicating potential lack of transparency.

📦 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 (315 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-dataexchange 
Your task is to create a Python-based mini-application named 'DataExchangeValidator' that leverages the 'aws-resource-validator-dataexchange' package to validate and manage resources from AWS Data Exchange. This application will serve as a tool for developers and system administrators to ensure compliance and integrity of their AWS Data Exchange resources. Here’s a detailed breakdown of what your application should include:

1. **Setup**: Begin by installing the necessary packages including 'aws-resource-validator-dataexchange'. Ensure that you have the correct version of Pydantic installed as it's required for the models.

2. **Resource Validation**: Implement functionality to validate AWS Data Exchange resources against predefined schemas provided by the 'aws-resource-validator-dataexchange' package. Your app should accept resource configurations as input and return validation results indicating whether each configuration adheres to the specified schema.

3. **Configuration Management**: Allow users to define custom validation rules or modify existing ones using the models provided by the package. This feature should enable flexibility in how resources are validated based on specific business requirements.

4. **Report Generation**: Create a feature that generates detailed reports summarizing the validation outcomes. These reports should be easily readable and provide insights into which resources passed or failed validation and why.

5. **Integration with AWS Services**: Optionally, integrate your application with AWS services such as S3 or Lambda to automatically validate resources whenever they are updated or created, ensuring continuous compliance.

6. **User Interface**: Develop a simple command-line interface (CLI) for interacting with the application. The CLI should allow users to perform actions like validating resources, setting up custom validation rules, and generating reports.

7. **Documentation**: Provide comprehensive documentation explaining how to install and use the application, including examples and best practices for integrating it into existing workflows.

By completing these steps, you'll have built a powerful tool that enhances the management and security of AWS Data Exchange resources.

💬 Discussion Feed

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