avaframe

v2.0.1 safe
4.0
Medium Risk

The Open Avalanche Framework

🤖 AI Analysis

Final verdict: SAFE

The package shows low risks across all categories except for metadata, where there are some concerns regarding incomplete maintainer information and lack of HTTPS links. However, these do not indicate any malicious intent.

  • No network or shell risks detected.
  • Metadata contains some suspicious elements but no clear signs of malice.
Per-check LLM notes
  • Network: No network calls detected, which is low risk.
  • Shell: Subprocess execution detected but no specific malicious intent identified from the given snippet.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting no risk of secret theft.
  • Metadata: Suspicious due to lack of HTTPS links and incomplete maintainer information, but no clear indicators of malicious intent.

📦 Package Quality Overall: Low (2.4/10)

○ 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 (867 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ 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 score 2.0

Found 1 shell execution pattern(s)

  • the subprocess process = subprocess.Popen( command, stdout=subprocess.PIPE, st
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: avaframe.org>

⚠ Suspicious Page Links score 6.0

Found 3 suspicious link(s) on the package page

  • Non-HTTPS external link: http://docs.avaframe.org**
  • Non-HTTPS external link: http://docs.avaframe.org/en/latest/
  • Non-HTTPS external link: http://avaframe.org
✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ 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 avaframe 
Create a mini-application called 'AvalancheRiskAssessor' using the Python package 'avaframe'. This tool aims to help users assess avalanche risks in specific geographic locations based on real-time data inputs. Here’s a step-by-step guide on how to develop this application:

1. **Setup**: Begin by installing 'avaframe' and any necessary dependencies for your project. Make sure you have access to real-time weather data APIs, which will be crucial for input into your risk assessment model.
2. **Data Input Module**: Develop a module within your application that allows users to input geographical coordinates of interest and select a date range for analysis. Additionally, integrate functionality to pull real-time weather data from public APIs such as OpenWeatherMap or similar services.
3. **Risk Assessment Engine**: Utilize 'avaframe' to process the collected data through its avalanche risk assessment algorithms. Ensure your application can interpret and display the output in a user-friendly manner, highlighting critical factors like snow depth, temperature, wind speed, and direction.
4. **Visualization Interface**: Implement a graphical interface where users can visualize the risk assessment results. Use maps to show the geographical areas at risk, color-coded to indicate severity levels (low, medium, high).
5. **User Notifications**: Add a feature allowing users to set up alerts for specific avalanche risk thresholds. When these thresholds are met, users should receive notifications via email or SMS.
6. **Documentation & User Guide**: Provide comprehensive documentation and a user guide explaining how to use the application effectively, including tips on interpreting risk assessments and safety precautions.

Suggested Features:
- Historical data comparison to current risk assessment
- Interactive map exploration for different locations
- Detailed explanations of risk factors and their impact
- Integration with social media platforms for sharing findings

Remember, the key to this application is leveraging 'avaframe' to provide accurate and actionable information to users about avalanche risks. Ensure that your implementation is robust, scalable, and user-friendly.

💬 Discussion Feed

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