AI Analysis
The package shows low risks in terms of network, shell, obfuscation, and credential misuse, but the metadata risk score is elevated due to the maintainer's new or inactive account and lack of detailed information.
- Maintainer has a new or inactive account
- Lack of proper author name
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 immediate risk from command injection.
- Obfuscation: No obfuscation patterns detected, indicating likely legitimate use without hidden code.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
- Metadata: The maintainer has a new or inactive account with limited package history and lacks a proper author name.
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 (288 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 command-line utility named 'FMSHealthChecker' that leverages the 'aws-resource-validator-fms' package to validate AWS Firewall Manager resources against predefined Pydantic models. This utility will help system administrators ensure their AWS FMS resources comply with organizational policies and best practices. The application should perform the following steps: 1. Authenticate using AWS credentials stored in environment variables or a configuration file. 2. Retrieve a list of all AWS FMS resources from the specified AWS account. 3. Validate each resource against the Pydantic models provided by 'aws-resource-validator-fms'. 4. Output a report detailing which resources passed validation and which did not, along with specific reasons for failure if applicable. 5. Optionally, allow users to specify custom validation rules by providing additional Pydantic models. 6. Provide options for output formats such as JSON, CSV, or plain text. 7. Implement error handling to manage issues like invalid AWS credentials or network errors when fetching resources. 8. Include a help menu with usage instructions and examples. Use the 'aws-resource-validator-fms' package to define and validate the structure and content of AWS FMS resources. This ensures that the resources adhere to expected standards, enhancing security and compliance within the AWS environment.
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