aws-resource-validator-support

v2.0.3 suspicious
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk indicators but raises concerns due to the sparse author information and potentially inactive maintenance.

  • Sparse author information
  • Potentially inactive maintainer
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 of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not pose a threat for stealing secrets or credentials.
  • Metadata: The author's information is sparse and the maintainer seems new or inactive, raising some suspicion but not definitive proof 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 (300 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-support 
Create a Python-based mini-application named 'AWS Support Validator' that leverages the 'aws-resource-validator-support' package to validate AWS resource configurations against Pydantic v2 models. This tool will help developers ensure their AWS resources adhere to best practices and compliance standards before deployment. The application should include the following features:

1. **Resource Configuration Input**: Users should be able to input their AWS resource configurations either through a command-line interface or a simple GUI. These configurations could be in YAML or JSON format.
2. **Validation Engine**: Utilize the Pydantic v2 models provided by the 'aws-resource-validator-support' package to validate the input configurations. Ensure that the validation checks cover all necessary aspects such as required fields, data types, and constraints.
3. **Error Reporting**: If any issues are found during the validation process, the application should report these errors in a user-friendly manner, highlighting which part of the configuration is incorrect and why.
4. **Configuration Fixing Suggestions**: For each error reported, provide suggestions on how to fix the configuration. This feature should aim to guide users towards a valid configuration without having to manually figure out the fixes.
5. **Report Generation**: After the validation process, generate a comprehensive report summarizing the status of the validation (whether it passed or failed), listing all errors encountered, and providing overall feedback on the configuration's quality.
6. **Integration Testing**: Include a set of predefined test cases (valid and invalid configurations) to demonstrate the functionality of the validator. These tests should cover a variety of scenarios to ensure robustness.
7. **Documentation**: Provide clear documentation on how to use the application, including setup instructions, a description of the validation rules applied, and examples of valid and invalid configurations.

This mini-application will serve as a valuable tool for developers working with AWS resources, ensuring that their configurations meet the necessary standards and reducing the likelihood of deployment issues due to configuration errors.

💬 Discussion Feed

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