arize-otel

v0.13.0 suspicious
4.0
Medium Risk

Helper package for OTEL setup to send traces to Arize & Phoenix

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network calls, shell executions, obfuscations, and credential harvesting. However, the metadata risk score is elevated due to the maintainer's new or inactive account and lack of proper author information, suggesting potential suspicious activity.

  • metadata risk due to new/inactive maintainer account
  • lack of proper maintainer author name
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 immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate a low-risk but suspicious activity.

📦 Package Quality Overall: Medium (6.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.arize.com/arize/large-language-models/tracing
  • Detailed PyPI description (16858 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 22 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 10 unique contributor(s) across 19 commits in Arize-ai/arize-otel-python
  • Active community — 5 or more distinct contributors

🔬 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: arize.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Arize-ai/arize-otel-python 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 arize-otel 
Create a simple web application using Flask that integrates the 'arize-otel' package to monitor its performance and errors in real-time. This application will serve as a basic calculator that supports addition, subtraction, multiplication, and division operations. Additionally, it will have a feature to log user interactions and errors to ensure smooth operation and quick debugging. Here are the steps to develop this project:

1. Set up a new Flask application.
2. Install the 'arize-otel' package and configure it to connect to your Arize and Phoenix instances.
3. Implement the calculator functionalities (addition, subtraction, multiplication, division).
4. Integrate the 'arize-otel' package to trace each request made to the calculator API endpoints and log any exceptions that occur during computation.
5. Extend the functionality to include logging of user interaction data such as timestamp, user IP address, and the operation performed.
6. Test the application thoroughly, ensuring that all traces and logs are correctly sent to Arize and Phoenix.
7. Document the setup process and how to interpret the logs and traces provided by Arize and Phoenix for monitoring and debugging purposes.

Suggested Features:
- Real-time visualization of request processing times.
- Alerting mechanism for high error rates or slow response times.
- Detailed breakdown of errors and their occurrence frequency.
- Ability to filter logs based on user IP addresses or specific time ranges.

By following these steps, you'll create a fully functional mini-application that not only performs basic arithmetic operations but also provides valuable insights into its operational health through the use of 'arize-otel'.

💬 Discussion Feed

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