AI Analysis
The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential harvesting attempts. The metadata risk is slightly elevated due to limited author information.
- No network calls detected
- Sparse author information
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 risk of executing system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author information is sparse, indicating potential lack of transparency or a new/inactive account.
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 (357 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 'AppRegistryChecker' that leverages the 'aws-resource-validator-servicecatalog-appregistry' package to validate resources within the AWS Service Catalog App Registry. This tool should allow users to input specific Application IDs or import their details from a CSV file. For each Application ID provided, the tool will fetch and validate the associated resources against predefined schemas using the pydantic models included in the 'aws-resource-validator-servicecatalog-appregistry' package. Additionally, it should offer options to filter results based on resource types or tags, and generate a summary report at the end of the validation process. Users should also have the ability to save the validation results to a specified output file. The application should handle exceptions gracefully and provide meaningful error messages when issues arise during the validation process.
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