aws-resource-validator-mq

v2.0.3 safe
4.0
Medium Risk

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

🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious intent with very low risks across all categories except metadata, where the maintainer's account status is concerning. However, the absence of any network, shell, or obfuscation risks makes it unlikely to be a supply-chain attack.

  • Low network risk
  • Low shell risk
  • Low obfuscation risk
  • Low credential risk
  • Moderate metadata risk due to maintainer's account status
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 no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which could indicate a lower level of trustworthiness.

📦 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 (285 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-mq 
Create a Python-based utility named 'MQInspector' that leverages the 'aws-resource-validator-mq' package to validate and manage Amazon MQ resources efficiently. This tool will serve as a comprehensive solution for developers and DevOps engineers who need to ensure their Amazon MQ configurations adhere to best practices and standards.

### Key Features:
1. **Resource Validation**: Implement a feature that allows users to input details of an Amazon MQ resource configuration. The utility will then validate these inputs against predefined Pydantic models from the 'aws-resource-validator-mq' package to ensure all required fields are present and formatted correctly.
2. **Configuration Suggestions**: If any part of the input configuration is invalid or missing, provide suggestions on how to correct it based on the validation errors returned by the Pydantic models.
3. **Report Generation**: Upon successful validation, generate a detailed report that summarizes the validated configuration. This report should include key parameters such as broker type, engine type, storage type, and security group IDs.
4. **Interactive CLI**: Develop an interactive command-line interface (CLI) that guides users through the process of entering their Amazon MQ resource details and viewing the validation results.
5. **Integration with AWS SDK**: Integrate the utility with the AWS SDK for Python (Boto3) to allow for direct creation of valid Amazon MQ resources based on the validated configuration.

### How to Utilize 'aws-resource-validator-mq':
- Import and utilize the Pydantic models provided by 'aws-resource-validator-mq' to define the structure of Amazon MQ resources.
- Use these models to validate user inputs and generate meaningful error messages or suggestions for correction.
- Ensure that the generated report and the final resource creation steps are aligned with the validated configuration.

### Steps to Build 'MQInspector':
1. **Setup Environment**: Install necessary packages including 'aws-resource-validator-mq', Pydantic, and Boto3.
2. **Define Models**: Create classes for validating Amazon MQ resources using the models from 'aws-resource-validator-mq'.
3. **CLI Development**: Design and implement a CLI that accepts user inputs and interacts with the validation logic.
4. **Validation Logic**: Implement the validation logic that uses the defined models to check user inputs.
5. **Report Generation**: Write functions to generate and display the summary report.
6. **AWS Integration**: Optionally, integrate the utility with AWS services to create validated resources directly.
7. **Testing**: Test the utility thoroughly to ensure it works as expected and handles various edge cases gracefully.

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