aws-resource-validator-emr

v2.0.3 safe
3.0
Low Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity and appears to be legitimate. The metadata risk score is slightly elevated due to incomplete author information, but this alone does not indicate a supply-chain attack.

  • 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 communication.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting legitimate usage.
  • Metadata: The author information is incomplete, suggesting a potential lack of transparency or newness, but no other red flags were identified.

📦 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 (288 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-emr 
Create a mini-application named 'EMRResourceChecker' using Python that leverages the 'aws-resource-validator-emr' package. This tool aims to validate and manage resources related to Amazon EMR clusters. The application should have the following functionalities:

1. **Resource Validation**: Users should be able to input a configuration file (in YAML format) that describes their desired EMR cluster setup. Your application will use the 'aws-resource-validator-emr' package to validate this configuration against predefined Pydantic models, ensuring that all specified resources comply with AWS EMR standards.

2. **Cluster Creation Assistance**: If the configuration passes validation, your app should provide suggestions on how to optimize the resource allocation for better performance or cost-efficiency based on user-defined criteria (e.g., budget constraints, required processing power).

3. **Error Reporting**: In case of validation errors, the app should clearly report which fields are incorrect and why, guiding users towards correcting their configurations.

4. **Integration with AWS SDK**: For demonstration purposes, include a feature that allows users to create an actual EMR cluster based on the validated configuration, using the Boto3 library. Note: This feature should be optional and require explicit user consent due to security reasons.

5. **User Interface**: Develop a simple command-line interface (CLI) for interacting with the application. Ensure it's user-friendly, providing clear instructions and feedback throughout the process.

6. **Documentation**: Write comprehensive documentation detailing how to install the app, configure it, and use its features effectively.

In your implementation, focus on utilizing the 'aws-resource-validator-emr' package efficiently to demonstrate its capabilities in validating complex EMR configurations. Consider including examples in your documentation to help others understand how to use your application for different scenarios.

💬 Discussion Feed

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