appm

v0.3.0 suspicious
4.0
Medium Risk

APPN Phenomate Project Manager

πŸ€– AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risk in terms of network calls, shell execution, obfuscation, and credential handling. However, the metadata quality is poor, raising concerns about the developer's intentions or professionalism.

  • Low metadata quality
  • Potential lack of developer commitment
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external API interactions.
  • Shell: No shell execution patterns detected, indicating the package does not attempt to execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The package shows low effort in maintaining metadata and author details, which raises some suspicion but does not conclusively indicate malice.

πŸ“¦ Package Quality Overall: Low (2.8/10)

β—‹ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
β—ˆ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (6808 chars)
β—‹ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β—ˆ Medium Type Annotations 5.0

Partial type annotation coverage

  • 22 type-annotated function signatures detected in source
β—‹ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked β€” contributor count unavailable

πŸ”¬ Heuristic Checks

βœ“ Outbound Network Calls

No suspicious network call patterns found

βœ“ Code Obfuscation

No obfuscation patterns detected

βœ“ Shell / Subprocess Execution

No shell execution patterns detected

βœ“ Credential Harvesting

No credential harvesting patterns detected

βœ“ Typosquatting

No typosquatting candidates detected

βœ“ Registered Email Domain

No author email provided

βœ“ Suspicious Page Links

All external links appear legitimate

βœ“ 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 short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
βœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

πŸ’‘ AI App Starter Prompt

Use this prompt to build a project with appm
Create a task management mini-app using the 'appm' package, which stands for APPN Phenomate Project Manager. This mini-app will allow users to manage their tasks efficiently by adding, deleting, updating, and listing tasks. Additionally, users should be able to categorize tasks into different projects and set deadlines for each task. Here’s a detailed step-by-step guide on how to develop this mini-app:

1. **Project Setup**: Start by setting up your Python environment and installing the 'appm' package. Use pip to install it if it’s not already installed.
2. **User Interface Design**: Design a simple yet intuitive command-line interface (CLI) where users can interact with the app. Ensure that the CLI supports basic commands like 'add', 'delete', 'update', 'list', and 'set deadline'.
3. **Task Management Features**: Implement core functionalities such as adding new tasks with descriptions, deleting tasks, updating task details, and listing all tasks. Each task should have a unique identifier.
4. **Project Categorization**: Allow users to assign tasks to different projects. Projects should also be manageable through the CLI, enabling users to add, delete, and list projects.
5. **Deadline Management**: Integrate functionality to set deadlines for tasks. Users should be able to view upcoming deadlines and get notifications about tasks that are approaching their deadlines.
6. **Data Persistence**: Use 'appm' to handle data persistence. Ensure that tasks and projects are saved and can be retrieved even after the app is closed and reopened.
7. **Error Handling**: Implement robust error handling to manage invalid inputs gracefully and provide meaningful feedback to the user.
8. **Testing**: Write unit tests for all functionalities to ensure they work as expected. Focus on edge cases to improve the reliability of the app.
9. **Documentation**: Document your code thoroughly and provide a README file explaining how to use the app and its features.

The 'appm' package will be primarily used for managing the storage and retrieval of tasks and projects. It simplifies the process of storing complex hierarchical data structures, making it easier to implement features like categorizing tasks under projects and managing deadlines. Utilize the package’s documentation to understand how to integrate these features effectively into your mini-app.

πŸ’¬ Discussion Feed

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