🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits low risks in terms of network, shell, and obfuscation activities, but its metadata suggests it may be poorly maintained or abandoned, which raises concerns about its reliability and security over time.

Low metadata quality indicating potential lack of maintenance.
No direct security threats identified.

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communication.
Shell: No shell execution patterns detected, indicating the package does not attempt to execute commands on the system.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low effort and potential lack of maintenance, raising suspicion but not conclusive evidence of malice.

🔬 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: utu.fi>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
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 PyROTS

Create a mini-application called 'ROTS Explorer' that allows users to interact with the ROTS system using the PyROTS Python package. This application will serve as a user-friendly interface to explore and manipulate data through the ROTS API. Here are the steps and features to implement:

1. **Setup**: Begin by installing the necessary packages including PyROTS. Ensure your environment is set up properly to handle Python requests and responses.
2. **Authentication Module**: Implement a secure authentication module where users can log in using their credentials provided by the ROTS system. Store tokens securely for subsequent requests.
3. **Data Exploration Interface**: Design an intuitive interface for exploring data available through the ROTS API. Users should be able to view different datasets and their attributes.
4. **Data Manipulation Tools**: Allow users to perform basic operations such as filtering, sorting, and aggregating data based on specific criteria.
5. **Visualization Feature**: Integrate visualization capabilities to help users understand the data better. This could include charts and graphs generated from the data retrieved via PyROTS.
6. **Export Functionality**: Enable users to export the manipulated data into common file formats like CSV or Excel for further analysis outside the application.
7. **User Guide and Documentation**: Provide comprehensive documentation explaining how to use each feature of the ROTS Explorer application effectively.

In each of these steps, utilize the core functionalities of PyROTS to interact with the ROTS system, ensuring that all operations are performed efficiently and securely.