AI Analysis
Final verdict: SUSPICIOUS
The package shows signs of typosquatting targeting 'nox' and has a recently created repository with rapid commits, suggesting potential malicious intent.
- Typosquatting attempt targeting 'nox'
- Recent repository creation with rapid commits
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: Highly suspicious due to recent repository creation and rapid commits, along with a single package upload from a new maintainer account.
- ⚠ Typosquatting target: nox
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
score 3.0
Possible typosquat of: nox
"n4ax" is 2 edit(s) from "nox"
Registered Email Domain
Email domain looks legitimate: gragas.ai>
Suspicious Page Links
All external links appear legitimate
Git Repository History
score 5.0
Git history flags: Repository created very recently: 1 day(s) ago (2026-06-04T17:47:58Z)
Repository created very recently: 1 day(s) ago (2026-06-04T17:47:58Z)All 6 commits happened within 24 hours
Maintainer History
score 6.0
3 maintainer concern(s) found
Only one version has ever been released — brand new packagePackage uploaded less than 24 hours ago (2026-06-05T09:40:12.000Z)Author "Geoffroy Oudoumanessah, Jacopo Iollo" appears to have only 1 package on PyPI (new or inactive account)
AI App Starter Prompt
Use this prompt to build a project with n4ax
Create a medical imaging tool using Python that leverages the 'n4ax' package to correct intensity non-uniformity in MRI scans. This tool should be designed to assist radiologists and medical researchers in improving the quality of their images for better diagnostic outcomes. The application will have a user-friendly command-line interface where users can input the path to their MRI scan files. The tool should also allow users to specify parameters such as the number of iterations and smoothing factor for the correction process. Additionally, the application should output both the corrected image and a plot showing the estimated bias field. To enhance usability, include a feature that allows users to compare the original and corrected images side-by-side. Utilize the 'n4ax' package's capabilities to ensure the application is efficient and can handle large datasets typical in medical imaging.