🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with a low risk score due to the absence of network calls, shell execution, obfuscation, and credential harvesting patterns. However, there are some concerns regarding metadata completeness and link security.

No network calls or shell executions detected.
Incomplete maintainer information and potentially insecure links.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network functionality.
Shell: No shell execution patterns detected, indicating no immediate signs of malicious shell command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
Metadata: The package shows some signs of potential risk due to incomplete maintainer information and insecure links, but no clear indicators of malicious intent.

🔬 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: iac.es>

⚠ Suspicious Page Links score 4.0

Found 2 suspicious link(s) on the package page

Non-HTTPS external link: http://img.shields.io/badge/license-GPLv3-blue.svg?style=flat
Non-HTTPS external link: http://www.gnu.org/licenses/gpl-3.0.html

✓ Git Repository History

Repository hpparvi/ExoIris 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 ExoIris

Create a Python-based mini-application called 'ExoSpectroViewer' which leverages the ExoIris package to visualize and analyze exoplanet transmission spectra. This application should allow users to upload their own data or select from preloaded datasets of exoplanet transit light curves. Users should be able to manipulate these datasets to generate transmission spectra and analyze the resulting data. Key features include:

1. User Interface: Develop a simple yet intuitive GUI using Tkinter or Streamlit.
2. Data Input: Allow users to upload their own .csv files containing time-series photometric data or select from predefined datasets.
3. Spectrum Generation: Utilize ExoIris functions to process the uploaded data and generate transmission spectra.
4. Interactive Analysis: Implement interactive elements such as zooming, panning, and cursor tracking on the spectral plots.
5. Saving Results: Provide functionality to save the generated spectra and analysis results.
6. Documentation: Include comprehensive documentation within the code and a user guide explaining each feature and how to use ExoIris.

The application should demonstrate the power of ExoIris in handling real-world astronomical data, making it accessible and understandable to both amateur astronomers and researchers.