AI Analysis
Final verdict: SUSPICIOUS
The package has a moderate risk score due to potential code obfuscation techniques and low maintainer activity, though there are no direct indicators of malicious behavior or credential theft.
- High obfuscation risk due to use of eval
- Low maintainer activity and poor metadata quality
Per-check LLM notes
- Network: No network calls detected, which is normal for a plotting library unless it requires external data sources.
- Shell: No shell execution patterns detected, indicating the package does not execute external commands.
- Obfuscation: The use of eval with restricted globals may indicate an attempt to obfuscate code execution, which is a common technique in malicious packages.
- Credentials: No clear patterns indicative of credential harvesting were detected.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising some suspicion but not definitive evidence of malicious intent.
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
_eval_globals() arr = eval(text, allowed_globals, local_vars) return _coerce_resul
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 6.0
3 maintainer concern(s) found
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 JarvisPLOT
Create a data visualization dashboard app using Python that leverages the JarvisPLOT package for dynamic plotting based on user input. Your task is to develop an interactive tool that allows users to upload their dataset in CSV format, select specific columns for plotting, choose from various plot types supported by JarvisPLOT (such as line plots, bar charts, histograms), and customize plot aesthetics via YAML configuration files. Additionally, the app should offer real-time feedback through tooltips displaying detailed information about data points when hovering over them in the plot. Users should also have the ability to save their customized plots directly to their local storage. This project aims to showcase the flexibility and power of JarvisPLOT in handling complex visualizations driven by user preferences and external configurations.