AI Analysis
The package presents minimal risks based on the analysis notes. It lacks network calls, shell executions, obfuscations, and shows no signs of credential harvesting.
- Low network risk
- No shell risk
- Minimal obfuscation risk
- No credential risk
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external API interactions.
- Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has an incomplete profile and seems new or inactive, but there are no clear signs of malicious intent.
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 (330 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 command-line tool that leverages the 'aws-resource-validator-globalaccelerator' package to validate and manage AWS Global Accelerator resources efficiently. This tool should allow users to perform the following actions: 1. **Resource Validation**: Users should be able to input details of their AWS Global Accelerator resources (such as accelerators, listeners, endpoints) via the command line, and the tool will use the pydantic models provided by 'aws-resource-validator-globalaccelerator' to validate these inputs against AWS specifications. 2. **Resource Creation/Update**: After validation, if the resource details are correct, the tool should then use the AWS SDK (boto3) to create or update the corresponding AWS Global Accelerator resources based on the validated data. 3. **Resource Deletion**: Provide functionality to delete specific AWS Global Accelerator resources based on user input. 4. **Resource Listing**: Implement a feature to list all currently active AWS Global Accelerator resources associated with the user's account. 5. **Interactive Mode**: Offer an interactive mode where users can navigate through different operations without having to restart the tool. 6. **Logging and Error Handling**: Ensure that all interactions with AWS services are logged, and errors are handled gracefully, providing meaningful error messages to the user. The 'aws-resource-validator-globalaccelerator' package plays a crucial role in this project by ensuring that all resource configurations adhere strictly to AWS standards before any creation or update operations are performed. This not only enhances the reliability of the tool but also simplifies the process of managing complex AWS Global Accelerator setups.
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