atoti-client

v0.9.15 suspicious
4.0
Medium Risk

Code to interact with an Atoti session

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risk in terms of network and shell activity, and there's no sign of code obfuscation or credential harvesting. However, the metadata risk score is moderately high due to the maintainer having only one package, which raises concerns about the maintainer's credibility.

  • Metadata risk due to single package from maintainer
  • Lack of description and version history
Per-check LLM notes
  • Network: No network calls detected, which is normal for a client library unless it requires API interactions.
  • Shell: No shell execution detected, which is expected as direct system command execution is not typical for a client library.
  • 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 (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 
Your task is to develop a Python-based mini-application that serves as a data analysis dashboard using the 'atoti-client' package. This application will allow users to connect to an existing Atoti session, load data into it, perform various types of analysis, and visualize the results in real-time. Here are the steps and features you need to implement:

1. **Project Setup**: Begin by setting up your Python environment. Ensure that 'atoti-client' is installed via pip.
2. **Connecting to Atoti Session**: Implement a function to connect to an existing Atoti session. This function should accept credentials and session details as parameters.
3. **Data Loading**: Create a feature that allows users to upload CSV or Excel files directly through the application interface. Once uploaded, the application should automatically load this data into the Atoti session.
4. **Interactive Data Exploration**: Provide a user-friendly interface where users can explore the loaded data interactively. They should be able to filter data based on specific criteria and view summary statistics.
5. **Custom Analysis**: Allow users to define custom analyses using SQL-like queries or pre-defined templates within the application. These analyses should update in real-time as data changes.
6. **Visualization**: Integrate visualizations such as charts and graphs directly into the application to help users better understand their data. Visualizations should dynamically update based on the selected filters and analyses.
7. **Real-Time Collaboration**: Enable multiple users to collaborate in real-time on the same dataset. Users should be able to see each other's actions and updates instantly.
8. **Exporting Results**: Finally, provide an option for users to export their analysis results, either as a PDF report or downloadable CSV file.

Throughout the development process, ensure that you leverage the core functionalities provided by 'atoti-client', such as session management, data manipulation, and interactive analytics capabilities. Your goal is to create a tool that not only showcases the power of 'atoti-client' but also provides significant value to users looking to analyze and share data efficiently.

💬 Discussion Feed

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