AI Analysis
Final verdict: SUSPICIOUS
The package shows low risk in terms of network, shell, obfuscation, and credential risks. However, the metadata risk is elevated due to an unnamed author and a new/inactive account, which warrants further investigation.
- Unnamed author
- New or inactive account
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires online functionality.
- Shell: No shell execution detected, indicating no immediate risk of command injection or similar attacks.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package has some red flags including an author with no name and a new/inactive account, but no typosquatting or suspicious links were detected.
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: ironsoftware.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 IronXL
Create a fully-functional mini-application named 'ExcelDataProcessor' using the Python package 'IronXL'. This application will serve as a versatile tool for managing Excel files, including reading, writing, and performing basic data manipulations. The primary goal of this project is to demonstrate the capabilities of IronXL in handling complex Excel operations efficiently. ### Application Overview: - **Functionality**: The app will allow users to import an existing Excel file, perform various data operations such as filtering, sorting, and aggregation, and then save the modified data back into a new Excel file. - **User Interface**: A simple command-line interface (CLI) will be sufficient for this application. - **Features**: - Importing an Excel file (.xlsx format). - Displaying the content of the imported Excel file. - Filtering rows based on user-defined criteria. - Sorting columns based on user-selected column names. - Aggregating data (e.g., summing up values in specific columns). - Exporting the processed data into a new Excel file. - Handling errors gracefully (e.g., incorrect file formats, missing data). ### Utilization of IronXL: - Use IronXL to read Excel files into memory for manipulation. - Apply IronXL's filtering and sorting functions to process the data according to user commands. - Use IronXL to write the processed data back into a new Excel file. - Leverage IronXL’s error-handling mechanisms to ensure robustness. ### Steps to Develop the Application: 1. **Setup Environment**: Install necessary packages, including IronXL, pandas, and any other dependencies. 2. **Import and Display Data**: Write a function to import an Excel file using IronXL and display its contents. 3. **Implement Data Processing Functions**: Create functions for filtering, sorting, and aggregating data based on user inputs. 4. **Export Processed Data**: Implement functionality to save the processed data back into an Excel file. 5. **Testing and Debugging**: Test the application with various Excel files and ensure it handles all types of user input and errors correctly. 6. **Documentation**: Provide clear documentation on how to use the CLI, including examples and common issues. This project aims to provide a practical example of using IronXL for real-world data processing tasks, showcasing its efficiency and ease of use.