AI Analysis
The package shows no immediate signs of malicious activity such as network calls, shell executions, or credential harvesting. However, the metadata risk score is elevated due to sparse author information and possibly inactive account status.
- No network calls or shell executions detected
- Sparse and potentially inactive author account
Per-check LLM notes
- Network: No network calls detected, which is expected for a package that does not require external API interactions.
- Shell: No shell execution patterns detected, indicating the package does not perform any system-level commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
- Metadata: The author information is sparse and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.
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 (327 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 content validation tool named 'MediaValidator' using the 'aws-resource-validator-mediapackage-vod' package. This tool will help content creators ensure their MediaPackage VOD (Video On Demand) resources meet specific criteria before publishing. The application should perform the following tasks: 1. **Resource Validation**: Use the Pydantic models from 'aws-resource-validator-mediapackage-vod' to validate MediaPackage VOD resources against predefined schemas. 2. **Error Reporting**: Provide a user-friendly report listing any issues found during the validation process. 3. **Interactive Mode**: Allow users to interactively input resource details and receive instant feedback on validation status. 4. **Batch Processing**: Enable users to upload a file containing multiple resources and validate them all at once. 5. **Custom Rules**: Support customization of validation rules based on specific requirements or compliance standards. 6. **Integration with AWS SDK**: Integrate with the Boto3 library to fetch and validate existing MediaPackage VOD resources directly from AWS. 7. **Logging and Audit Trail**: Implement logging functionality to keep track of validation activities and results for audit purposes. Your task is to design and implement this tool, ensuring it leverages the 'aws-resource-validator-mediapackage-vod' package effectively for resource validation. Document your implementation steps, including setup instructions, code snippets showcasing key functionalities, and usage examples.
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