🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has moderate network risk due to external server communication, but low risks in other categories. The new or inactive maintainer and lack of community engagement raise additional concerns, warranting further investigation before use.

Moderate network risk
Inactive or new maintainer
Lack of community engagement

Per-check LLM notes

Network: The network calls indicate the package communicates with external servers which could be legitimate for functionality but also raises concerns about data privacy and potential misuse.
Shell: No shell execution patterns detected, suggesting low risk for direct system command injection or execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer seems new or inactive, and the repository lacks community engagement, raising some concerns but not definitive signs of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

turn False response = requests.get( f"{self.portal_url}/sdk/check_test/",
str, Any]: response = requests.get( f"{self.portal_url}/computableModel/ModelInfo_n
turn False response = requests.get( f"{self.manager_url}/GeoModeling/task/verify/{m
as fh: response = requests.post( f"{self.data_url}/data/", f
.{suffix}" response = requests.get(url, timeout=120) response.raise_for_status()
} response = requests.post( f"{cfg.dify_base_url.rstrip('/')}/workflows/run

✓ 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: nnu.edu.cn

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Peilong Ma" 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 PyGeoModel

Create a geospatial data explorer app using Python and the PyGeoModel package. This app will allow users to interactively explore various geographic models provided by the OpenGMS platform. Your task is to develop a user-friendly interface where users can select different geographic regions and visualize corresponding models, including but not limited to terrain elevation, land use, and climate zones. The app should also enable users to download selected model data for further analysis. Here’s a detailed breakdown of the requirements:

1. **User Interface Design**: Design a clean and intuitive UI using a framework like Tkinter or PyQt. The UI should include options for selecting geographic regions and models.
2. **Integration with PyGeoModel**: Use PyGeoModel to fetch geographic model data from the OpenGMS API. Ensure that you handle authentication if required by the API.
3. **Data Visualization**: Implement a feature to visualize the fetched geographic models on a map. Libraries like Matplotlib or GeoPandas can be used for this purpose.
4. **Download Functionality**: Allow users to download the selected model data in formats such as CSV or shapefiles.
5. **Error Handling**: Implement robust error handling to manage issues like network errors, invalid inputs, etc.
6. **Documentation**: Provide comprehensive documentation explaining how to install dependencies, run the app, and interpret the visualizations.

Suggested Features:
- Support for multiple geographic models per region.
- Interactive zoom and pan functionality on the map.
- Tooltip information for each model displayed when hovering over specific areas.
- Option to overlay multiple models on the same map for comparative analysis.

Remember to utilize PyGeoModel effectively throughout the development process to ensure seamless integration with the OpenGMS services.