astroeasy

v1.1.0 suspicious
5.0
Medium Risk

Astrometry.net made easy - plate solving and index management

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows legitimate functionality but raises concerns due to high shell risk and a potentially suspicious metadata profile.

  • High shell risk due to Docker usage
  • Suspicious maintainer metadata
Per-check LLM notes
  • Network: Network calls could be legitimate for fetching resources related to astronomy.
  • Shell: Executing shell commands, especially involving Docker, may indicate complex operations but also potential for misuse.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The maintainer has a new or inactive account with limited package history and lacks a full author name, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 9 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 9 test file(s) detected (e.g. __init__.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/zgazak/astroeasy#readme
  • Detailed PyPI description (6457 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

  • 72 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 14 commits in zgazak/astroeasy
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • ing from {url}") with urllib.request.urlopen(url, timeout=60) as response: with open(
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • ve-field command r1 = subprocess.run( base_docker_command + solve_field_command.split
  • fication command r2 = subprocess.run( base_docker_command + verify_command.split(),
  • ew container result = subprocess.run( ["docker", "run", "--rm", image, "solve-field",
  • d_command}") result = subprocess.run( solve_field_command.split(), captur
  • tion command result = subprocess.run( verify_command.split(), capture_out
  • ch" location_result = subprocess.run([which_cmd, "solve-field"], capture_output=True, text=True)
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: alum.mit.edu>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository zgazak/astroeasy 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 astroeasy 
Create a desktop application named 'SkyMapper' using Python that simplifies the process of identifying celestial objects from photographs taken through telescopes or cameras. This app will utilize the 'astroeasy' package to perform plate-solving on images and manage indices of known celestial objects.

### Project Overview:
- **Name:** SkyMapper
- **Purpose:** To enable amateur astronomers and enthusiasts to easily identify stars, galaxies, nebulae, and other celestial bodies from their own photos.
- **Platform:** Desktop application (cross-platform)

### Core Features:
1. **Image Upload:** Users should be able to upload astronomical images directly from their devices or via drag-and-drop functionality.
2. **Plate Solving:** Utilize 'astroeasy' to automatically solve the uploaded image, determining its orientation and scale relative to the night sky.
3. **Object Identification:** After plate solving, the application should overlay known celestial objects on the image based on its solved coordinates.
4. **Index Management:** Implement a feature that allows users to add their own annotated images to a personal index, which can then be used for future reference.
5. **User Interface:** Design a clean, intuitive UI that includes tools for zooming, panning, and marking areas of interest within the image.
6. **Export Options:** Provide options for exporting the annotated image or a report detailing the identified celestial objects.

### Detailed Steps:
1. **Setup Environment:** Begin by setting up a Python environment and installing necessary packages including 'astroeasy', 'PIL' for image processing, and 'tkinter' for the GUI.
2. **Develop Image Uploading Mechanism:** Create a user-friendly interface for uploading images. Ensure it supports various file formats commonly used in astronomy.
3. **Implement Plate Solving Functionality:** Use 'astroeasy' to solve the uploaded images. This involves calling functions from the package to analyze the image and return celestial coordinates.
4. **Overlay Objects on Image:** Once coordinates are determined, fetch data from an astronomical database or API to overlay names and details of recognized objects onto the image.
5. **Personal Index Management:** Allow users to save their images with annotations into a local database or file system for future use.
6. **Design User Interface:** Develop a graphical interface that integrates all functionalities smoothly, ensuring ease of use and accessibility.
7. **Testing & Deployment:** Thoroughly test the application under different scenarios to ensure reliability. Prepare for deployment as a standalone executable.

### Expected Outcome:
Upon completion, 'SkyMapper' will be a powerful yet simple tool for astronomers and enthusiasts alike, significantly reducing the complexity involved in analyzing and understanding astronomical images.

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