ACID-code

v0.1.0 suspicious
5.0
Medium Risk

Returns line profiles from input spectra by fitting the stellar continuum and performing LSD

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has no signs of malicious intent or obfuscation but lacks detailed metadata, which raises some concerns about its legitimacy and maintenance efforts.

  • Low effort in metadata and maintainer history
  • No detected malicious patterns
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows low effort in metadata and maintainer history, which could indicate potential risk.

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ACID-code 
Create a mini-application called 'SpectralAnalyzer' using Python and the ACID-code package. This application will serve as a powerful tool for astronomers and researchers to analyze stellar spectra by extracting line profiles. Here's a step-by-step guide on how to develop this application:

1. **Project Setup**: Start by setting up a new Python virtual environment and installing necessary packages including ACID-code.
2. **Data Input**: Allow users to upload their own spectral data files (e.g., FITS files). Ensure that the application can handle multiple file formats.
3. **Stellar Continuum Fitting**: Utilize ACID-code's capabilities to fit the stellar continuum to the uploaded spectra. Implement different methods for continuum fitting and allow users to choose the best method based on their data characteristics.
4. **Line Profile Extraction**: Using the fitted continuum, extract line profiles from the input spectra. ACID-code's LSD (Least Squares Deconvolution) feature should be prominently used here.
5. **Visualization**: Provide visual representations of the original spectra, the fitted continuum, and the extracted line profiles. Use libraries like Matplotlib or Seaborn for plotting.
6. **Results Export**: Enable users to export the analyzed results in various formats such as CSV, PNG, or PDF.
7. **User Interface**: Develop a simple yet intuitive GUI using PyQt or Tkinter to make the application user-friendly. Alternatively, consider building a web-based interface using Flask or Django for wider accessibility.
8. **Documentation and Help**: Include comprehensive documentation and help sections within the application to guide users through each step of the process.

Additional Features to Consider:
- Interactive plots where users can zoom in/out and pan across the spectrum.
- Option to save intermediate steps and resume analysis later.
- Integration with cloud storage services for easy sharing and collaboration.
- Real-time feedback during the analysis process.

Ensure that throughout the development process, you leverage ACID-code's core functionalities to provide accurate and efficient spectral analysis.

💬 Discussion Feed

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