AI Analysis
Final verdict: SAFE
The package presents minimal risks as it does not engage in network calls, shell executions, or obfuscations. While there are some concerns regarding metadata quality and maintainer activity, these alone do not indicate malicious intent.
- Low risk scores across all technical categories
- Metadata quality and maintainer activity are questionable but lack clear indicators of malicious behavior
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating no direct command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows some signs of low maintainer activity and poor metadata quality, but lacks clear indicators of malicious intent.
Package Quality Overall: Low (1.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.headfirstlabs.com
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "akash" 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 akashprajapati-nester-20262027
Create a Python-based command-line utility named 'NestedListPrinter' that leverages the 'akashprajapati-nester-20262027' package to print out nested lists in a user-friendly format. The utility should accept input from the user in the form of a string representation of a nested list and then use the 'nester' function provided by the package to print it out in an indented format, making complex nested structures more readable. ### Features: 1. **Input Parsing:** The utility should be able to parse various types of nested list inputs from the user, including lists containing numbers, strings, and other lists. 2. **Pretty Printing:** Utilize the 'nester' function from 'akashprajapati-nester-20262027' to print the nested list in an indented format. Each level of nesting should be visually distinguished by indentation. 3. **Error Handling:** Implement error handling to manage invalid inputs gracefully, providing meaningful error messages to the user. 4. **Custom Indentation:** Allow users to specify the number of spaces for indentation, enhancing the flexibility of the output format. 5. **Save Output:** Include an option for users to save the formatted output to a file, allowing them to keep a record of the printed nested list structure. ### Steps to Build the Utility: 1. Install the 'akashprajapati-nester-20262027' package using pip. 2. Design a simple CLI interface that prompts the user for the nested list input and any optional parameters such as custom indentation or saving to a file. 3. Parse the input string into a Python list object, ensuring to handle different data types within the list. 4. Call the 'nester' function from 'akashprajapati-nester-20262027' with the parsed list and any specified indentation settings. 5. Implement error handling to catch and report any parsing errors or issues with the 'nester' function execution. 6. Add functionality to write the formatted output to a file if the user chooses to do so. 7. Test the utility with various nested list inputs to ensure robustness and usability.