AI Analysis
Final verdict: SAFE
The package shows low risk indicators with no network calls, shell executions, or obfuscations. However, it appears to be a typosquatting attempt targeting 'doit', and the maintainer's metadata suggests a new or less active account.
- Low risk scores across all categories
- Potential typosquatting
- New or less active maintainer
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 direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has a low number of packages and lacks PyPI classifiers, indicating potential low effort or new account status.
- ⚠ Typosquatting target: doit
Package Quality Overall: Low (3.8/10)
◈ Medium
Test Suite
6.0
Partial test coverage signals detected
Test runner config found: pyproject.toml
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (1151 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
15 type-annotated function signatures detected in source
○ 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
score 3.0
Possible typosquat of: doit
"aokit" is 2 edit(s) from "doit"
Registered Email Domain
Email domain looks legitimate: huggingface.co>
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 "cbensimon, sayakpaul" 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 aokit
Create a fully functional mini-application that leverages the 'aokit' package for ahead-of-time (AOT) compilation of Python code. Your application will serve as a basic static site generator that converts Markdown files into HTML pages. This utility will be particularly useful for bloggers and content creators who want to quickly convert their blog posts from Markdown format into a static HTML format without needing to run any server-side code on each request. Here’s a detailed breakdown of what your application should include: 1. **Application Setup**: Start by setting up a new Python environment. Install necessary packages including 'aokit' and any other dependencies like 'markdown2' for converting Markdown to HTML. 2. **Directory Structure**: Define a simple directory structure where input Markdown files are placed in a folder named 'content', and output HTML files are saved in a folder named 'output'. 3. **Markdown to HTML Conversion**: Use 'markdown2' to convert Markdown files into HTML. Ensure that the conversion process includes options to customize the HTML output, such as adding custom CSS classes or headers. 4. **Ahead-of-Time Compilation with AOKIT**: Utilize 'aokit' to compile the Python function responsible for converting Markdown to HTML into an optimized binary. This step ensures that the conversion process is as fast as possible when running the application. 5. **Command Line Interface (CLI)**: Develop a CLI tool that allows users to specify which Markdown files to convert and where to save the resulting HTML files. The CLI should also provide an option to run the compiled binary for faster execution. 6. **Customization Options**: Allow users to customize the HTML templates used for conversion through configuration files. This way, users can tailor the look and feel of their generated HTML pages. 7. **Testing and Documentation**: Write tests to ensure that the conversion process works correctly and that the compiled binary behaves as expected. Provide comprehensive documentation on how to use the application, including setup instructions, usage examples, and troubleshooting tips. 8. **Deployment Considerations**: Discuss how this application could be deployed in different environments, such as local machines, cloud services, or even as part of a larger web application stack. Highlight the benefits of using AOT compilation in these scenarios. By following these steps, you'll create a versatile tool that demonstrates the power of 'aokit' for optimizing Python applications.
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