axiom-py

v0.12.0 suspicious
4.0
Medium Risk

Official bindings for the Axiom API

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential misuse due to incomplete metadata and communication with an external service, although there is no concrete evidence of malicious intent.

  • Incomplete author metadata
  • Communication with an external service
Per-check LLM notes
  • Network: The network calls suggest the package is designed to communicate with an external service, which is not inherently malicious but requires verification of its intended use.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's name is missing and they appear to be new or inactive, raising some suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

  • 11 test file(s) detected (e.g. helpers.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (3500 chars)
○ 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

  • 86 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 15 unique contributor(s) across 100 commits in axiomhq/axiom-py
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • port requests resp = requests.get( f"{os.getenv('AXIOM_URL')}/v1/datasets/{cls.dat
  • client self.client = httpx.AsyncClient( base_url=url.rstrip("/"), timeout=D
✓ 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository axiomhq/axiom-py appears legitimate

⚠ 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)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with axiom-py 
Create a real-time data logging and visualization tool using Python and the 'axiom-py' package. This tool will allow users to input various types of data (e.g., temperature readings, stock prices, sensor outputs) into a live dashboard that updates in real-time. Here’s a step-by-step guide on how to build it:

1. **Setup Environment**: Begin by setting up your Python environment. Ensure you have the latest version of Python installed along with 'axiom-py'. You can install 'axiom-py' via pip.

2. **Data Collection**: Implement a simple interface where users can input different types of data. For example, they could enter temperature readings from sensors or stock prices from financial APIs. This data should be stored locally before being sent to Axiom.

3. **Axiom Integration**: Use 'axiom-py' to send collected data to an Axiom database. Make sure to handle authentication properly by following Axiom’s guidelines for secure API usage.

4. **Real-Time Dashboard**: Develop a web-based dashboard using a framework like Flask or Django. This dashboard should fetch data from the Axiom database in real-time and display it in a visually appealing manner. Consider using libraries such as Plotly or Matplotlib for dynamic visualizations.

5. **User Interface Enhancements**: Add features to the dashboard such as filters, time range selection, and different chart types (line graphs, bar charts, etc.). Also, include options for users to customize their view.

6. **Security and Privacy**: Ensure that all data transmissions are encrypted and that user privacy is respected. Provide clear instructions on how to manage data securely within Axiom.

7. **Testing and Deployment**: Thoroughly test your application to ensure it works as expected under various conditions. Once satisfied, deploy your application to a cloud service provider of your choice.

8. **Documentation**: Write comprehensive documentation explaining how to set up and use your application. Include examples of how to integrate it with external data sources.

This project aims to demonstrate the power of real-time data processing and visualization while showcasing the capabilities of the 'axiom-py' package.

💬 Discussion Feed

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