atoti-server-jdbc

v0.9.15 suspicious
3.0
Low Risk

Resources to interact with databases through JDBC

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network usage, shell execution, and code obfuscation. However, the maintainer's single-package presence raises a flag, warranting further scrutiny.

  • Maintainer has only one package
  • 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 command execution from the 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 might 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-jdbc 
Develop a data analysis dashboard using Python that connects to a PostgreSQL database via JDBC to retrieve real-time financial market data. This application will allow users to visualize stock prices, trading volumes, and other key metrics over time. Utilize the 'atoti-server-jdbc' package to establish the connection between your Python environment and the database. The dashboard should include interactive charts for users to explore trends and patterns in the data. Key features of the application include:

1. **Data Retrieval**: Use 'atoti-server-jdbc' to connect to a PostgreSQL database where historical and live financial market data is stored. Ensure the connection supports real-time updates.
2. **Visualization**: Implement visualizations such as line graphs for stock price trends and bar charts for trading volumes. Users should be able to select different stocks and time periods dynamically.
3. **Real-Time Updates**: Enable the dashboard to automatically refresh data from the database every minute, ensuring that users always have access to the latest information.
4. **User Interface**: Design a clean and intuitive user interface using a Python library like Streamlit or Dash. Allow users to input stock symbols and date ranges directly within the app.
5. **Error Handling**: Implement robust error handling to manage potential issues such as database connectivity problems or invalid user inputs.
6. **Documentation**: Provide comprehensive documentation on setting up the PostgreSQL database, configuring the 'atoti-server-jdbc' package, and deploying the application.

This project aims to demonstrate the power of combining Python's data analysis capabilities with real-time database interactions via JDBC, making it a valuable tool for finance professionals and enthusiasts alike.

💬 Discussion Feed

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