ast-tool-py

v0.27.15 suspicious
4.0
Medium Risk

Asterix data processing tool

๐Ÿค– AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in direct threat indicators like network, shell, and obfuscation but has a moderate metadata risk due to the unavailability of the repository and the new/inactive maintainer account.

  • Metadata risk score is high due to missing repository and new/inactive maintainer
  • No direct threat indicators like network calls or shell executions were detected
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
  • Shell: No shell execution patterns 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 repository is not found and the maintainer has a new or inactive account with minimal information.

๐Ÿ“ฆ Package Quality Overall: Low (2.8/10)

โ—‹ Low Test Suite 1.0

No test suite detected

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

Some documentation present

  • Detailed PyPI description (34208 chars)
โ—‹ Low Contributing Guide 2.0

No contributing guide or governance files found

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

Partial type annotation coverage

  • 40 type-annotated function signatures detected in source
โ—‹ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

๐Ÿ”ฌ Heuristic Checks

โœ“ Outbound Network Calls

No suspicious network call patterns found

โœ“ Code Obfuscation

No obfuscation patterns detected

โœ“ Shell / Subprocess Execution

No shell execution patterns detected

โœ“ Credential Harvesting

No credential harvesting patterns detected

โœ“ Typosquatting

No typosquatting candidates detected

โœ“ Registered Email Domain

Email domain looks legitimate: via.si>

โœ“ Suspicious Page Links

All external links appear legitimate

โš  Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
โš  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)
โœ“ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

๐Ÿ’ก AI App Starter Prompt

Use this prompt to build a project with ast-tool-py 
Create a Python-based mini-application named 'AsterixDataAnalyzer' that leverages the 'ast-tool-py' package for processing and analyzing datasets stored in the AsterixDB format. This application will serve as a powerful tool for data scientists and analysts who need to quickly process large volumes of semi-structured data. Here are the key steps and features your application should include:

1. **Setup and Installation**: Begin by setting up a virtual environment for your project and installing the necessary dependencies, including 'ast-tool-py'. Ensure you have the latest version of Python installed.

2. **Connecting to AsterixDB**: Develop a connection module within 'AsterixDataAnalyzer' that allows users to connect to their AsterixDB instance. This module should handle authentication and error handling gracefully.

3. **Query Execution**: Implement a feature that enables users to execute SQL-like queries on their AsterixDB datasets directly from the application. Users should be able to specify the dataset they want to query and receive the results in a structured format.

4. **Data Transformation**: Utilize 'ast-tool-py' to transform raw query results into more usable formats such as CSV, JSON, or Pandas DataFrames. This transformation should be customizable based on user preferences.

5. **Visualization Tools**: Integrate basic visualization capabilities using libraries like Matplotlib or Seaborn. These visualizations should be directly tied to the transformed data, allowing users to quickly analyze trends and patterns.

6. **Error Handling and Logging**: Ensure robust error handling throughout the application, logging any issues encountered during execution to a log file. This will help maintain system reliability and provide insights for debugging.

7. **User Interface**: While not mandatory, consider developing a simple command-line interface (CLI) or a graphical user interface (GUI) using Tkinter for interacting with 'AsterixDataAnalyzer'. This will make the application more accessible to users without extensive programming knowledge.

Throughout the development process, focus on leveraging 'ast-tool-py' for its core functionalities, particularly in data transformation and analysis tasks. This will not only enhance the application's performance but also showcase the capabilities of the package in real-world scenarios.

๐Ÿ’ฌ Discussion Feed

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