NREL-landbosse

v2.6.3 safe
3.0
Low Risk

Wind-Plant Integrated System Design & Engineering Model

🤖 AI Analysis

Final verdict: SAFE

The package exhibits low risks across all evaluated categories except metadata, where there are some concerns about the maintainer's account status.

  • No network or shell execution detected.
  • No signs of obfuscation or credential harvesting.
  • Maintainer's metadata shows potential unreliability.
Per-check LLM notes
  • Network: No network calls detected, which is normal for a package that does not require external data or services.
  • Shell: No shell execution patterns detected, indicating the package does not execute external commands, which is typical for a software tool focused on its intended functionality.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, which could indicate a lower level of trustworthiness.

🔬 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: nlr.gov>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository NLRWIndSystems/LandBOSSE 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 NREL-landbosse 
Develop a comprehensive wind farm design tool using the NREL-landbosse Python package. This tool will serve as a decision support system for renewable energy consultants and engineers, enabling them to evaluate different site conditions and configurations for wind farms. The application should include the following key features:

1. **Site Data Input**: Allow users to input or upload data about their potential wind farm site, including geographical coordinates, terrain elevation maps, and local weather patterns.
2. **Wind Turbine Selection**: Provide a database of available wind turbine models with specifications such as rotor diameter, hub height, and power output. Users should be able to select one or more turbines for their simulation.
3. **Simulation Execution**: Utilize NREL-landbosse to run simulations based on the user inputs. The tool should calculate expected energy production, costs, and environmental impacts over a specified period.
4. **Visualization**: Offer graphical representations of the simulation results, including maps showing wind farm layouts, bar charts displaying annual energy production, and cost breakdowns.
5. **Report Generation**: Automatically generate detailed reports summarizing the simulation outcomes, which can be exported as PDF files for further analysis or presentation purposes.
6. **Scenario Comparison**: Enable users to compare multiple scenarios by adjusting variables like turbine type, layout, or site modifications, and visualize the impact on overall performance.
7. **User Interface**: Develop an intuitive web-based interface built with Flask or Django, making it easy for non-experts to interact with the tool.
8. **Documentation**: Include thorough documentation explaining how to use the tool, interpret the results, and integrate it into existing workflows.

The goal is to create a user-friendly yet powerful application that leverages NREL-landbosse’s capabilities to provide valuable insights into wind farm design and operation.