AI Analysis
The package has low risks in terms of network activity, shell execution, and obfuscation. However, it exhibits moderate metadata issues which raise suspicion about its origins or maintenance practices.
- Low metadata quality
- Potential proxy usage
Per-check LLM notes
- Network: No network calls suggest normal operation if the package is not designed to communicate externally.
- Shell: No shell executions indicate that the package does not execute external commands, which is typical for a library focused on core functionality.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no attempt at stealing secrets.
- Metadata: The package shows some red flags such as low metadata quality and potential proxy usage, but lacks clear indicators of malicious intent.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (6704 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
78 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
No author email provided
Found 2 suspicious link(s) on the package page
Non-HTTPS external link: http://usuario:[email protected]:3128Non-HTTPS external link: http://proxy.empresa:3128
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "Ampere Consultoria Empresarial LTDA" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a fully functional mini-application using the 'ampere-core-sdk' Python package. This application will serve as a basic inventory management system for a small retail store. The system should allow users to manage product listings, track stock levels, and handle basic sales transactions. The application should include the following core functionalities: 1. Product Management: Users should be able to add new products, update existing product information, and delete products from the inventory. 2. Stock Management: The application should keep track of the current stock level for each product and alert users when stock levels fall below a certain threshold. 3. Sales Transactions: Allow users to process sales transactions, which will decrease the stock level of sold items accordingly. 4. Reporting: Provide a feature to generate simple reports on sales performance and stock levels. Utilize the 'ampere-core-sdk' package to structure your application according to the hexagonal architecture principles (domain, application, infrastructure). Ensure that the domain layer contains all business logic, the application layer handles use cases, and the infrastructure layer manages data access and other external services. Your task is to design and implement this application, adhering strictly to the guidelines provided by the 'ampere-core-sdk'. Additionally, ensure that the application is well-documented and includes tests for its core functionalities.
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