AI Analysis
Final verdict: SUSPICIOUS
The package has low risks associated with network, shell execution, obfuscation, and credential harvesting. However, incomplete maintainer information raises concerns about potential inactivity or lack of transparency.
- Incomplete maintainer information
- Low risk indicators across other categories
Per-check LLM notes
- Network: No network calls suggest the package does not engage in external communications which could be used for malicious activities.
- Shell: No shell executions indicate that the package is not executing system commands, reducing the risk of it being used to perform unauthorized actions on the host.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity.
- Metadata: The maintainer's author information is incomplete and they may be new or inactive, raising some suspicion but not conclusive evidence of malice.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository Centurix/injectinator appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with Injectinator
Create a simple task management application using Python, where you will utilize the 'Injectinator' package for dependency injection. This application should allow users to create, view, update, and delete tasks. Each task should have a title, description, due date, and status (e.g., pending, completed). Step 1: Define your task model class. This class should contain attributes like title, description, due_date, and status. Step 2: Implement a service layer for interacting with these tasks. This could include methods such as add_task(), get_tasks(), update_task(), and delete_task(). These services will depend on a repository layer for data storage and retrieval. Step 3: Use 'Injectinator' to manage dependencies between your service layer and repository layer. For example, when creating an instance of your service class, you should be able to inject a specific implementation of the repository interface. Suggested Features: - Ability to filter tasks based on their status. - Support for setting reminders for upcoming due dates. - A command-line interface for user interaction. How to Utilize 'Injectinator': - First, define your interfaces and concrete classes for the repository layer. - Then, use 'Injectinator' to configure and inject the appropriate repository implementation into your service layer during initialization. This allows for easy swapping out of different repository implementations if needed (for example, switching from an in-memory storage to a database storage). - Ensure that your application demonstrates the flexibility and ease of use provided by 'Injectinator' through clear examples within your code.