AI Analysis
Final verdict: SAFE
The package has minimal risks associated with obfuscation and credential harvesting. While there is some concern regarding metadata and maintainer history, these alone do not indicate malicious intent or a supply-chain attack.
- Low obfuscation risk
- Low credential risk
- Concerns about metadata quality and maintainer history
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low effort in metadata and maintainer history, but lacks clear indicators of malicious intent.
Package Quality Overall: Low (1.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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 apheris-utils
Create a fully-functional mini-app that helps manage tasks and projects for a team using the 'apheris-utils' Python package. This app will serve as a simple project management tool, allowing users to create, edit, delete, and view tasks, as well as assign these tasks to different team members. Here’s a detailed plan on how to build it: 1. **Setup Environment**: Begin by setting up your development environment with Python installed. Make sure you have the 'apheris-utils' package installed via pip. 2. **Application Structure**: Design the basic structure of your application. Decide whether you want a command-line interface (CLI) or a graphical user interface (GUI). For simplicity, let's start with a CLI. 3. **Core Features**: - **Task Creation**: Users should be able to create new tasks with details like title, description, due date, and priority level. - **Task Editing**: Allow users to edit any task's details, including its status (e.g., in progress, completed). - **Task Deletion**: Provide functionality to remove tasks from the system. - **View Tasks**: Implement a feature to display all tasks, optionally filtering by status or assigned member. - **Assign Tasks**: Enable assigning tasks to specific team members. 4. **Utilizing 'apheris-utils'**: Use the 'apheris-utils' package to handle common utilities such as logging, configuration management, and possibly data validation. For example, use 'apheris-utils.logging' to log important actions like task creation and deletion, and 'apheris-utils.config' to manage application settings and preferences. 5. **Additional Enhancements**: Consider adding extra functionalities like sending notifications when a task's due date is approaching, or integrating a simple search function to find tasks based on keywords. 6. **Testing**: Thoroughly test your application to ensure all features work as expected. Pay special attention to edge cases, such as what happens if a user tries to delete a non-existent task. 7. **Documentation**: Write clear documentation for both end-users and developers. Include setup instructions, a user guide, and API documentation if applicable. 8. **Deployment**: Once everything is tested and documented, consider deploying your application so others can use it. If you chose a CLI, you might distribute it as a Python package. If you went with a GUI, look into platforms for distributing desktop applications.