🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of risk with no network calls, shell executions, or obfuscations detected. While the metadata suggests a less experienced maintainer, there are no clear indications of malicious activity.

No network calls
No shell execution
No obfuscation

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
Shell: No shell execution patterns detected, indicating it does not execute external commands which reduces potential risks.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating secure handling of secrets and credentials.
Metadata: The maintainer seems new and there's low metadata effort, but no clear signs 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: gmail.com

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Jinseok Ryu" 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 CAETomo

Your task is to create a mini-application that leverages the capabilities of the 'CAETomo' package, which specializes in 1D-CAE embedded EELS tomography. This application will serve as a user-friendly interface for researchers and scientists to process and visualize Electron Energy Loss Spectroscopy (EELS) data using advanced computational methods. The goal is to streamline the workflow from raw data input to processed output, including visualization and analysis, thereby reducing the time and effort required for manual processing.

### Key Features:
1. **Data Input**: Allow users to upload their EELS data files. Ensure compatibility with common file formats used in EELS studies.
2. **Preprocessing**: Implement basic preprocessing steps such as background subtraction and normalization to prepare the data for analysis.
3. **Tomographic Reconstruction**: Utilize the 'CAETomo' package to perform the 1D-CAE embedded EELS tomography on the preprocessed data. This step involves applying the core algorithms of the CAETomo package to reconstruct the tomographic images.
4. **Visualization**: Provide tools for visualizing the reconstructed tomographic images. Include options for adjusting parameters like color scales, brightness, and contrast.
5. **Analysis Tools**: Offer basic analytical tools such as peak detection, spectral fitting, and comparison between different datasets.
6. **Output and Export**: Enable users to export the processed data and images in various formats suitable for further analysis or publication.
7. **User Interface**: Design a clean and intuitive user interface that guides users through each step of the process. Consider incorporating tooltips or help sections to assist with understanding the functionalities.

### How to Use 'CAETomo':
- Integrate 'CAETomo' into your application by installing it via pip or cloning its repository if necessary.
- Import the necessary modules from 'CAETomo' and use them to handle the core computations related to tomographic reconstruction.
- Ensure that the application calls the appropriate functions from 'CAETomo' during the tomographic reconstruction phase to leverage its specialized algorithms.

By completing this project, you'll not only gain experience with a unique scientific computing library but also contribute a valuable tool to the scientific community.