AI Analysis
Final verdict: SUSPICIOUS
The package shows no signs of immediate malicious activity such as network calls or shell executions. However, the metadata risk is high due to incomplete author information and rapid single-version uploads, which may indicate potential supply-chain risks.
- High metadata risk due to incomplete author details
- Single version upload within 24 hours
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution patterns detected, indicating the package does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: High risk due to new package with incomplete author information and single version upload within 24 hours.
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
score 3.0
Repository not found (deleted or private)
Repository not found (deleted or private)
Maintainer History
score 10.0
5 maintainer concern(s) found
Only one version has ever been released — brand new packagePackage uploaded less than 24 hours ago (2026-06-05T09:48:53.000Z)Author name is missing or very shortAuthor "" 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 scopos
Create a Python-based command-line tool named 'GPUWatch' that leverages the 'scopos' package to monitor and visualize GPU memory usage in real-time. This tool should display a Textual TUI interface that groups GPU memory usage statistics by user and provides a dynamic, interactive view of each user's GPU memory consumption over time. The application should allow users to filter by specific users, sort the displayed information based on different criteria such as memory usage percentage or total memory consumed, and provide alerts when certain thresholds of memory usage are exceeded. Additionally, include functionality to save historical data into a log file for later analysis. Ensure the application is user-friendly, with clear instructions and error handling for unexpected situations.