🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity such as network calls, shell execution, or obfuscation. However, the incomplete author's information and the maintainer having only one package raise concerns about potential supply-chain risks.

Incomplete author information
Maintainer has only one package

Per-check LLM notes

Network: No network calls suggest normal behavior unless the package is designed to be offline or its functionality does not require external communication.
Shell: No shell execution suggests the package does not attempt to execute commands on the host system, which is expected and safe.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The author's information is incomplete and the maintainer has only one package, which raises some suspicion.

🔬 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: visualtext.org>

⚠ Suspicious Page Links score 10.0

Found 5 suspicious link(s) on the package page

Non-HTTPS external link: http://vscode.visualtext.org
Non-HTTPS external link: http://talks.visualtext.org
Non-HTTPS external link: http://tutorials.visualtext.org
Non-HTTPS external link: http://visualtext.org
Non-HTTPS external link: http://nluglob.org

✓ Git Repository History

Repository VisualText/py-package-nlpengine appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 NLPPlus

Create a sentiment analysis tool using the Python package 'NLPPlus'. This tool will allow users to input text and receive a sentiment score indicating whether the text expresses positive, negative, or neutral sentiments. Additionally, the tool should categorize the input text into predefined categories such as politics, sports, entertainment, etc. The application should have a simple command-line interface for easy interaction.

Steps to create the tool:
1. Install the 'NLPPlus' package and import necessary modules for sentiment analysis and text categorization.
2. Design a function to accept user input through the command line.
3. Implement the sentiment analysis functionality using 'NLPPlus' to analyze the emotional tone of the input text.
4. Use 'NLPPlus' to categorize the text into one or more predefined categories based on its content.
5. Display the sentiment score and category(ies) back to the user in a clear, readable format.
6. Enhance the tool by adding error handling for invalid inputs and providing feedback messages.
7. Test the application with various types of texts to ensure it works correctly and efficiently.
8. Document the code and provide usage instructions for other developers.

Suggested Features:
- Support for multiple languages beyond English.
- Ability to adjust sensitivity levels for sentiment detection.
- Integration with a database to store and retrieve analyzed texts.
- Option to export results in CSV or JSON formats.