azkdutility

v1.0.2 suspicious
5.0
Medium Risk

Small utility set for aizakku.dev projects

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has no direct risks based on its functionality but exhibits suspicious metadata characteristics, suggesting potential malicious intent.

  • Low package activity
  • Lack of maintainer information
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external API interactions.
  • Shell: No shell execution detected, indicating 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 signs of potentially being used for malicious activities due to the low activity and lack of maintainer information.

📦 Package Quality Overall: Low (2.2/10)

○ 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
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 34 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 3 commits in aizakkuno/azkdutility
  • Single author with few commits — possibly a personal or throwaway project

🔬 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: aizakku.dev>

✓ 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
  • Single contributor with only 3 commit(s) — possibly throwaway account
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 azkdutility 
Create a fully-functional mini-app that integrates with the 'azkdutility' Python package to manage and display data from various sources. This app will serve as a versatile dashboard for monitoring and analyzing data across different platforms. Here are the key steps and features to implement:

1. **Setup**: Begin by installing the 'azkdutility' package. Ensure your development environment is configured correctly with Python 3.x.
2. **Data Sources Integration**: Use 'azkdutility' to connect to at least three different data sources (e.g., a local SQLite database, a remote API, and a CSV file). The package provides utilities to handle connections and data retrieval efficiently.
3. **Data Processing**: Implement functions within your app to process the retrieved data. Utilize 'azkdutility' for any necessary transformations or aggregations. For example, calculate average values, filter out irrelevant entries, or merge datasets from different sources.
4. **Visualization**: Create visual representations of the processed data using libraries like Matplotlib or Plotly. Integrate 'azkdutility' for any additional formatting or styling options available.
5. **User Interface**: Develop a simple web interface using Flask or Django where users can select which data source(s) they want to view and interact with the visualizations. Ensure the UI is responsive and user-friendly.
6. **Customization Options**: Allow users to customize the visualizations based on their preferences. They should be able to choose between different chart types (bar charts, line graphs, pie charts) and adjust colors, labels, etc.
7. **Export Functionality**: Add functionality that allows users to export the visualized data as images or PDFs. Use 'azkdutility' for any file handling tasks required.
8. **Testing and Documentation**: Thoroughly test your app to ensure all features work as expected. Document each step of the process, including setup instructions, usage examples, and troubleshooting tips.

By following these steps, you'll create a powerful yet easy-to-use data visualization tool that leverages the capabilities of 'azkdutility'.

💬 Discussion Feed

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