astro-gdt

v2.2.3 safe
3.0
Low Risk

Gamma-ray Data Tools: Core Components

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with low risks across multiple categories. The network calls and potential obfuscation techniques do not strongly indicate malicious intent given the context of the package's purpose.

  • Low network and shell execution risks
  • Potential obfuscation but within expected complexity for scientific tools
  • No evidence of credential or metadata abuse
Per-check LLM notes
  • Network: The network call may be legitimate if the package is designed to interact with remote servers, but it should be verified for its necessity and destination.
  • Shell: No shell execution patterns detected, indicating low risk.
  • Obfuscation: The code shows patterns that may be obfuscation techniques but could also be part of a complex algorithm implementation.
  • Credentials: No clear evidence of credential harvesting or secret handling is present in the provided snippets.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, but no other suspicious activities are flagged.

📦 Package Quality Overall: Medium (5.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://astro-gdt.readthedocs.io/en/latest/
  • Detailed PyPI description (1344 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 78 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 13 unique contributor(s) across 100 commits in USRA-STI/gdt-core
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • try: sock = socket.create_connection((host.split('/')[-1], 80)) sock.close()
⚠ Code Obfuscation score 10.0

Found 6 obfuscation pattern(s)

  • @abstractmethod def eval(self, params, x): # pragma: no cover """Evaluate th
  • s)[~free] return self.eval(full_params, x, **kwargs) def integrate(self, params, e
  • self._operator = [] def eval(self, params, x, components=False): """Evaluate the
  • [True, True, False] def eval(self, params, x): return params[0] * (x / params[2])
  • , True, True, False] def eval(self, params, x): A, Epeak, index, Epiv = params
  • , True, True, False] def eval(self, params, x): A, Epeak, alpha, beta, Epiv = para
✓ 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: usra.edu

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository USRA-STI/gdt-core appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "William Cleveland, Adam Goldstein, Daniel Kocevski" 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 astro-gdt 
Create a mini-application called 'GammaSkyExplorer' that allows users to analyze and visualize gamma-ray data from various astronomical sources. This application should utilize the 'astro-gdt' package to process and manipulate gamma-ray data efficiently. Here are the steps and features you should include:

1. **Data Importation**: Allow users to upload their own gamma-ray data files (e.g., FITS files) or select pre-existing datasets from a database included in the 'astro-gdt' package.
2. **Data Cleaning**: Implement a feature where 'astro-gdt' is used to clean and preprocess the data, removing any noise or irrelevant data points.
3. **Analysis Tools**: Integrate analysis tools provided by 'astro-gdt' to perform statistical analyses on the gamma-ray data, such as calculating fluxes, identifying sources, and detecting anomalies.
4. **Visualization Module**: Develop a visualization module that leverages 'astro-gdt' to create interactive plots and graphs of the analyzed data. Users should be able to customize these visualizations according to their preferences.
5. **Export Results**: Provide an option for users to export their analysis results and visualizations in various formats, such as PDF, PNG, or CSV.
6. **User Interface**: Design a user-friendly interface that guides users through each step of the process, from data importation to exporting results.
7. **Documentation and Help**: Include comprehensive documentation within the application that explains how to use each feature and provides examples of how to interpret the results.

This project aims to provide astronomers and researchers with a powerful yet accessible tool for analyzing and understanding gamma-ray data from celestial objects.

💬 Discussion Feed

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