🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal direct security risks, but concerns arise from incomplete metadata and low activity in the repository, suggesting potential maintenance issues.

Lack of maintainer information
Low activity in the git repository

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns 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 shows some red flags such as a lack of maintainer information and low activity in the git repository, but no clear signs of typosquatting or malicious intent.

🔬 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

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ 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 a11yviz

Create a web-based data visualization tool using Python that focuses on accessibility for users with visual impairments. Your tool should allow users to upload datasets and generate various types of plots such as line graphs, bar charts, and scatter plots using libraries like Plotnine and Plotly. The key requirement is to ensure that these visualizations are accessible according to the Web Content Accessibility Guidelines (WCAG 2.1). Utilize the 'a11yviz' package to enhance the accessibility of your visualizations.

Step-by-Step Instructions:
1. Set up a basic Flask or Django backend for handling user uploads and processing requests.
2. Integrate Plotnine and Plotly into your project for generating visualizations.
3. Use 'a11yviz' to make sure your visualizations are compliant with WCAG 2.1 standards, including providing alternative text descriptions, ensuring sufficient color contrast, and offering keyboard navigation options.
4. Implement a feature where users can download their visualizations in a format that includes accessibility enhancements, such as SVGs with embedded metadata.
5. Develop a frontend interface using HTML, CSS, and JavaScript (with frameworks like React or Vue if preferred) that allows users to interact with the data and view the generated visualizations.
6. Ensure all elements of the frontend are also WCAG 2.1 compliant, focusing on aspects like readable fonts, high contrast colors, and semantic HTML.
7. Test your application thoroughly to ensure that it meets the accessibility requirements and functions well across different devices and browsers.
8. Document your code and include a README file detailing how to run your application and any specific considerations for maintaining accessibility.