AI Analysis
The package has minimal risks associated with network, shell, and obfuscation activities. However, there is some concern about the metadata due to incomplete author information and potentially low activity from the author.
- Minimal risk in network, shell, and obfuscation activities.
- Metadata risk due to incomplete author information.
Per-check LLM notes
- Network: No network calls detected, which is expected for a package focused on local validation of AWS resources.
- Shell: No shell execution patterns detected, consistent with a package designed to operate without invoking system commands.
- Obfuscation: No obfuscation patterns detected, suggesting normal and transparent code practices.
- Credentials: No credential harvesting patterns detected, indicating safe handling of any potential secrets.
- Metadata: The author's information is incomplete and they appear to be a new or inactive user.
Package Quality Overall: Low (3.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Brief PyPI description (321 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Active multi-contributor project
4 unique contributor(s) across 75 commits in CoreOxide/aws_resource_validatorSmall but multi-author team (3–4 contributors)
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Repository CoreOxide/aws_resource_validator appears legitimate
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based CLI tool named 'ServiceCatChecker' that leverages the 'aws-resource-validator-servicecatalog' package to validate AWS Service Catalog resources. This tool should enable users to input specific AWS Service Catalog resource details and receive validation feedback on their configuration, ensuring compliance with best practices and standards. Step 1: Setup - Initialize a new Python project and install necessary dependencies including 'aws-resource-validator-servicecatalog'. Step 2: Define Core Functionality - Implement functions within 'ServiceCatChecker' to parse user input for AWS Service Catalog resource configurations. - Use the 'aws-resource-validator-servicecatalog' package to validate these configurations against predefined schemas. Step 3: User Interface - Develop a simple command-line interface (CLI) that prompts users for required inputs (e.g., ARN, resource type). - Display validation results in a user-friendly manner, highlighting any issues found during the validation process. Suggested Features: - Support for multiple AWS regions. - Option to validate configurations against different versions of AWS Service Catalog schemas. - Detailed error reporting including suggestions for corrections. - Integration with AWS SDK for fetching live data and comparing it against the provided configurations. Utilization of 'aws-resource-validator-servicecatalog': - The package provides Pydantic v2 models which are used to define and validate the structure of AWS Service Catalog resources. These models ensure that the input configurations adhere to expected formats and standards, facilitating a robust validation process.
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