aind-tars-service-client

v0.1.5 suspicious
3.0
Low Risk

aind-tars-service

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits unusually low activity in terms of network calls and maintenance, alongside missing standard metadata, which raises concerns about its legitimacy and purpose.

  • Low network activity
  • Low maintenance activity
  • Lack of standard metadata
Per-check LLM notes
  • Network: No network calls detected, which is unusual but not necessarily indicative of malicious activity without context.
  • Shell: No shell execution patterns detected, suggesting the package does not attempt to execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows low maintenance activity and lacks standard metadata, raising some suspicion but not conclusive evidence of malintent.

📦 Package Quality Overall: Low (3.6/10)

✦ High Test Suite 9.0

Test suite present — 17 test file(s) found

  • 17 test file(s) detected (e.g. test_alias.py)
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 58 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 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: openapitools.org

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "OpenAPI Generator community" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aind-tars-service-client 
Create a real-time data processing mini-application using the Python package 'aind-tars-service-client'. This application will simulate a scenario where a laboratory environment needs to collect and process sensory data from various experimental setups in real-time. The application should have the following core functionalities:

1. **Data Collection**: Simulate sensor data collection from different sources such as temperature sensors, light sensors, etc., and use the 'aind-tars-service-client' package to send this data to a central server for processing.
2. **Real-Time Processing**: Implement real-time processing of the collected data on the server side. This could include filtering out noise, identifying patterns, or calculating statistics.
3. **Data Visualization**: Provide a simple web-based interface for visualizing the processed data in real-time. Users should be able to see graphs and charts representing the data trends.
4. **Alert System**: If certain conditions are met (e.g., temperature exceeds a certain threshold), the application should trigger an alert via email or SMS.

The 'aind-tars-service-client' package will be primarily used for establishing connections with the server, sending raw sensor data, and receiving processed data back. Additionally, you should explore how the package supports error handling, retries, and other robustness features necessary for a production-grade application.

For the development environment, consider using Docker to containerize both the client and server components, ensuring compatibility across different systems. Use Flask for the web interface due to its simplicity and effectiveness for small projects.

This project aims to demonstrate the integration of IoT sensor data collection, real-time processing, and user-friendly visualization, all while leveraging the capabilities of 'aind-tars-service-client' for efficient data transmission.

💬 Discussion Feed

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