axis-prioris

v0.2.1 safe
3.0
Low Risk

Python client library for AXIS real-time information delivery service by Prioris

🤖 AI Analysis

Final verdict: SAFE

The package appears to be a legitimate client library for a specific service with low risk indicators across all categories.

  • Low network risk due to expected behavior
  • No signs of shell execution or obfuscation
  • Secure handling of credentials
Per-check LLM notes
  • Network: The observed network calls seem to be related to token refresh and server list retrieval, which could be legitimate if the package interacts with a service that requires authentication and communicates with multiple servers.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, suggesting secure handling of secrets.
  • Metadata: The maintainer seems new and has only one package, but no other suspicious activities are detected.

📦 Package Quality Overall: Low (3.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2125 chars)
○ 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

  • 27 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 15 commits in mugicomugi/axis.py
  • Single author with few commits — possibly a personal or throwaway project

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • """ try: resp = requests.get( TOKEN_REFRESH_URL, headers=_auth_he
  • """ try: resp = requests.get( SERVER_LIST_URL, headers=_auth_head
✓ 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 mugicomugi/axis.py appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "mugicomugi" 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 axis-prioris 
Create a real-time monitoring dashboard using the 'axis-prioris' Python package. This application will allow users to monitor various sensors and devices connected to the Prioris AXIS real-time information delivery service. The dashboard will display live data updates and provide historical data analysis capabilities.

**Features to Include:**
1. **Real-Time Data Visualization**: Implement a dynamic interface where users can view real-time data from different sensors and devices. Use libraries like Matplotlib or Plotly for graphing.
2. **Device Management**: Allow users to add, remove, and manage devices/sensors connected to the AXIS service through the 'axis-prioris' package.
3. **Historical Data Analysis**: Enable users to retrieve past data for analysis. Provide options to filter and visualize historical data based on user-defined criteria.
4. **Alert System**: Set up an alert system that triggers notifications when certain conditions are met (e.g., temperature exceeding a threshold).
5. **User Interface**: Design a clean, intuitive UI using a framework like Flask or Django for web-based access.

**Steps to Develop the Application:**
1. Install the 'axis-prioris' package and any additional required packages such as Matplotlib, Plotly, Flask/Django.
2. Authenticate with the Prioris AXIS service using the 'axis-prioris' package and establish a connection.
3. Fetch real-time data from connected devices and update the dashboard accordingly.
4. Implement device management functionalities allowing users to configure which devices they want to monitor.
5. Develop the historical data retrieval and visualization feature, ensuring users can easily analyze past performance.
6. Create an alert system that monitors data streams and sends alerts via email or SMS if predefined thresholds are exceeded.
7. Build a responsive UI with Flask or Django, incorporating all the above features into an easy-to-use dashboard.
8. Test the application thoroughly to ensure it functions correctly under various conditions and stress levels.
9. Deploy the application to a cloud service like AWS or Heroku for public accessibility.

💬 Discussion Feed

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