atoti-client-directquery-mssql

v0.9.15 suspicious
4.0
Medium Risk

Code to use DirectQuery on Microsoft SQL Server

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk in terms of network, shell, and obfuscation activities, but the metadata suggests the maintainer might be new or less active, raising some suspicion.

  • Metadata risk due to single package from maintainer
  • Lack of package description
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communication.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, suggesting a new or less active account which could be suspicious.

📦 Package Quality Overall: Low (4.2/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.activeviam.com/products/atoti/python-sdk/0.9.15
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • Two distinct contributors found

🔬 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: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" 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 atoti-client-directquery-mssql 
Create a mini-application that allows users to perform real-time data analysis directly from their Microsoft SQL Server database using the 'atoti-client-directquery-mssql' package. This application will serve as a bridge between the SQL Server and the user's interface, enabling them to execute complex queries and visualize the results without needing to download or transfer large datasets. Here’s a step-by-step guide on how to develop this application:

1. **Setup**: Begin by setting up your development environment. Ensure you have Python installed along with the necessary libraries including 'atoti-client-directquery-mssql'. You may also need additional packages such as Flask for web serving, Pandas for data manipulation, and Matplotlib/Seaborn for data visualization.

2. **Database Connection**: Use the 'atoti-client-directquery-mssql' package to establish a connection to the Microsoft SQL Server. This step involves specifying the server details, database name, and authentication credentials.

3. **Data Exploration Interface**: Develop an intuitive interface where users can input SQL queries directly or select pre-defined query templates. Ensure the interface supports auto-completion and syntax highlighting for better usability.

4. **Query Execution and Result Display**: Implement functionality within the application to execute the provided queries against the connected SQL Server database using the 'atoti-client-directquery-mssql' package. Display the results in a tabular format and allow users to export these results if needed.

5. **Visualization Tools**: Integrate tools within the application that allow users to visualize the query results. Users should be able to choose different types of charts (line graphs, bar charts, pie charts, etc.) based on the nature of their data.

6. **Advanced Features**: Consider adding advanced features such as saving frequently used queries, allowing users to create and manage personal dashboards, and providing options for exporting visualizations in various formats like PDF, PNG, or CSV.

7. **Security Measures**: Ensure that all user inputs are validated and sanitized to prevent SQL injection attacks. Also, implement secure authentication methods for accessing the application.

By following these steps, you'll create a powerful yet user-friendly tool that leverages the capabilities of the 'atoti-client-directquery-mssql' package to provide seamless and efficient access to data stored in Microsoft SQL Server.

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