atoti-server-directquery-mssql

v0.9.15 suspicious
4.0
Medium Risk

Resources to use DirectQuery on Microsoft SQL Server

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no direct signs of malicious intent such as network calls, shell executions, or credential harvesting. However, the lack of description and the maintainer having only one package contribute to a moderate level of suspicion.

  • No network calls detected
  • Maintainer has only one package
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity without further context.
  • Shell: No shell execution patterns detected, reducing the likelihood of immediate risk from this package.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which could indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.4/10)

○ 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 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-server-directquery-mssql 
Create a mini-application called 'SQL Data Explorer' that leverages the 'atoti-server-directquery-mssql' Python package to interact with Microsoft SQL Server databases using DirectQuery mode. This application will allow users to connect to their SQL Server databases, execute complex queries directly from the database without pulling all data into memory, and visualize query results in real-time.

Step 1: Set up the environment
- Install necessary packages including 'atoti-server-directquery-mssql', 'pandas', and 'matplotlib'.
- Configure the application to accept user input for SQL Server connection details (server name, database name, username, password).

Step 2: Connect to the SQL Server
- Use 'atoti-server-directquery-mssql' to establish a connection to the specified SQL Server database.
- Ensure the connection supports DirectQuery operations.

Step 3: Query Execution
- Allow users to input SQL queries directly into the application.
- Execute these queries against the connected database using DirectQuery.
- Handle any errors gracefully and provide feedback to the user.

Step 4: Visualization of Results
- Display the results of executed queries in a user-friendly format.
- Utilize 'matplotlib' to create charts and graphs based on the query results.
- Provide options to filter and sort the displayed data.

Suggested Features:
- Support for multiple concurrent connections to different SQL Servers.
- History of executed queries for quick recall and modification.
- Real-time updates as new data is added to the SQL Server.
- Export functionality to save query results and visualizations as CSV or image files.
- Advanced filtering options for query results, such as date ranges and value thresholds.

💬 Discussion Feed

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