AI Analysis
Final verdict: SUSPICIOUS
The package DIInjector v0.2 has minimal direct security risks, but its low maintainer activity and poor metadata quality raise concerns about potential supply-chain issues.
- Low maintainer activity
- Poor metadata quality
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires them.
- Shell: No shell executions detected, which indicates the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low maintainer activity and poor metadata quality, raising suspicion but not definitive 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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with DIInjector
Create a fully functional command-line utility named 'ServiceManager' that leverages the 'DIInjector' package to manage and interact with various services. This utility will allow users to register, start, stop, and query different services dynamically. Each service will represent a distinct functionality, such as logging, data processing, or file management. Here’s a detailed breakdown of the project requirements: 1. **Project Setup**: Initialize a new Python project with all necessary dependencies installed, including the 'DIInjector' package. 2. **Service Definition**: Define multiple services using classes. Each service should implement a common interface that includes methods like `start()`, `stop()`, and `status()`. 3. **Dependency Injection**: Use the 'DIInjector' package to inject dependencies into your services where needed. For example, a logging service might need an instance of a file handler or a database connection. 4. **Service Registry**: Implement a registry mechanism to keep track of registered services. Users should be able to add new services at runtime through the command line. 5. **Command Line Interface**: Develop a CLI that allows users to interact with the ServiceManager. Commands should include registering a new service, starting/stopping services, checking the status of all services, and listing all registered services. 6. **Dynamic Loading**: Enable the system to load services from external modules or files based on user input. 7. **Error Handling**: Ensure robust error handling for scenarios such as invalid commands, missing dependencies, or failed service operations. 8. **Documentation**: Provide comprehensive documentation explaining how to use the CLI, how to extend the system with new services, and how the 'DIInjector' package is utilized within the project. This project aims to demonstrate the power of dependency injection in managing complex applications while showcasing the capabilities of the 'DIInjector' package.