🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of obfuscation and credential harvesting, but the metadata suggests a lack of transparency with the maintainer's identity and account status, raising some suspicion.

Low obfuscation risk
Low credential risk
Metadata risk due to unclear maintainer information

Per-check LLM notes

Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate low activity or intent to remain anonymous.

🔬 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: geode-solutions.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Geode-solutions/PEGGHy-Viewer 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 PEGGHy-Viewer

Create a fully-functional mini-application called 'PEGGHy-Gallery' that leverages the capabilities of the 'PEGGHy-Viewer' package to display a gallery of images. This application should serve as a simple yet powerful tool for users to explore a curated collection of images from various sources. The application will be built using Python and will utilize Flask for web development. Here are the steps and features to implement:

1. **Setup Project Environment**: Begin by setting up your Python environment. Install necessary packages including Flask and PEGGHy-Viewer.
2. **Database Integration**: Integrate a database to store image metadata such as title, description, and source URL. SQLite could be a good choice for simplicity.
3. **Image Retrieval**: Use PEGGHy-Viewer's functionalities to retrieve images from the database. Ensure that the images are displayed in a clean, organized manner on the webpage.
4. **User Interface**: Design an intuitive user interface where users can browse through the gallery, view individual images, and access additional information about each image.
5. **Search Functionality**: Implement a search bar that allows users to find specific images based on keywords from the metadata.
6. **Pagination**: To improve navigation, add pagination so that images are shown in batches rather than all at once.
7. **Responsive Design**: Ensure the gallery is responsive, meaning it adjusts well to different screen sizes and devices.
8. **Error Handling**: Implement error handling to manage cases like missing images or database connection failures gracefully.
9. **Deployment**: Finally, deploy the application using a service like Heroku or AWS to make it accessible online.

Utilize PEGGHy-Viewer's core features to streamline the retrieval and display process of images, making sure the application is both efficient and user-friendly.