ankirai

v0.0.4 suspicious
6.0
Medium Risk

Transform your notes into Anki flashcards at lightning speed

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits a moderate level of risk, primarily due to its shell execution capability and potential credential harvesting mechanisms. While there is no direct evidence of malicious intent, the high metadata risk and recent rapid commit activity warrant caution.

  • Shell risk due to observed shell execution
  • Potential credential harvesting mechanism
Per-check LLM notes
  • Network: No network calls detected, which is typical and not indicative of malicious activity.
  • Shell: Shell execution observed may be intended for user interaction or configuration purposes but requires further investigation to ensure it's not being misused.
  • Obfuscation: No obfuscation patterns detected.
  • Credentials: The observed pattern suggests potential interactive input for an API key, which could be legitimate but also indicates risk of credential harvesting.
  • Metadata: High risk due to recent rapid commit activity, low maintainer history, and poor metadata quality.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 7 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (4917 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 29 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 16 commits in We-Gold/ankirai
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • viron.get("EDITOR", "vi") subprocess.call([editor, str(p)]) @prompt_group.command("reset") def promp
⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • )} API key" api_key = getpass.getpass(f"{label}: ").strip() base_url = "" default_model =
✓ 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 score 5.0

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • All 16 commits happened within 24 hours
⚠ 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)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ankirai 
Create a user-friendly desktop application called 'NoteToAnki' that transforms any set of notes into Anki flashcards with ease. This application will serve as a bridge between your note-taking habits and efficient learning through spaced repetition. Here's a step-by-step guide on how to build it:

1. **Application Setup**: Start by setting up your development environment. Ensure you have Python installed along with the necessary libraries such as `tkinter` for the GUI and `ankirai` for handling the conversion process.
2. **User Interface Design**: Design a simple yet intuitive interface where users can input their notes or upload a text file containing notes. Include fields for specifying the front and back sides of the flashcards if desired.
3. **Integration with Ankirai**: Utilize the `ankirai` package to convert the inputted notes into Anki-compatible flashcards. Explore its core functionalities like parsing notes into cards and customizing the format of these cards based on user preferences.
4. **Deck Management**: Allow users to choose which Anki deck they want to add the newly created flashcards to. If the specified deck does not exist, the app should automatically create it.
5. **Export Functionality**: Implement an export feature that allows users to save the generated Anki flashcards directly into their Anki collection file (.apkg).
6. **Additional Features**: Consider adding extra features such as the ability to schedule notifications for studying sessions based on the new flashcards, or integrating with popular note-taking apps to import notes directly.
7. **Testing and Feedback**: Test the application thoroughly with different types of notes and ensure that the flashcards are accurately created. Gather feedback from potential users to refine and improve the application further.
8. **Documentation and Deployment**: Write comprehensive documentation explaining how to use the application and how to install it. Deploy the application so that others can easily download and use it.

By following these steps, you'll develop a powerful tool that simplifies the process of converting notes into Anki flashcards, making learning more accessible and enjoyable.

💬 Discussion Feed

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