🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has minimal risks related to network calls, obfuscation, and credentials. However, the metadata risk score and potential misuse of shell commands raise suspicion about its integrity.

Low maintainer effort and suspicious author details
Shell execution for version checking and plugin execution

Per-check LLM notes

Network: No network calls detected, which is normal for this type of package.
Shell: Shell execution appears to be used for version checking and plugin execution review, which seems to be part of the package's functionality but should be reviewed further for safety.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer effort and suspicious author details, raising some concerns but not definitive proof of malicious intent.

📦 Package Quality Overall: Low (4.8/10)

◈ 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 (14801 chars)

◈ Medium Contributing Guide 7.0

Some contribution signals present

Governance file: security.py

◈ Medium Type Annotations 5.0

Partial type annotation coverage

222 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 score 10.0

Found 5 shell execution pattern(s)

ersion() -> str: result = subprocess.run( [sys.executable, "-m", "arweb", "--version"],
letedProcess[str]: return subprocess.run( command, cwd=cwd, env=env,
review = json.loads( subprocess.run( [sys.executable, "scripts/check_plugin_executi
tation = json.loads( subprocess.run( [sys.executable, "scripts/check_plugin_executi
enance = json.loads( subprocess.run( [sys.executable, "scripts/check_plugin_executi

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" 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 arabic-web-transpiler

Create a fully functional mini-app that allows users to input HTML, CSS, and JavaScript code written in Arabic and outputs the equivalent code in English, ready to be used in standard web development environments. This app will serve as a bridge between developers who prefer writing code in Arabic and those who work exclusively with English-based languages. Utilize the 'arabic-web-transpiler' Python package to handle the translation process. Here are the steps and features your application should include:

1. **User Interface**: Develop a clean, user-friendly interface where users can paste their HTML, CSS, and JavaScript code into separate text areas.
2. **Translation Engine**: Use the 'arabic-web-transpiler' package to convert the inputted Arabic code into its English equivalent. Ensure that the package correctly handles all necessary syntax transformations, including variable names, keywords, comments, and any specific characters unique to Arabic script.
3. **Syntax Highlighting**: Implement syntax highlighting for both the input and output text areas to improve readability and user experience.
4. **Real-time Preview**: Add a feature that provides a real-time preview of the translated code in action. This could be achieved by embedding a simple browser within the app that displays the HTML/CSS/JS content as it gets translated.
5. **Save & Share**: Allow users to save their translated code snippets locally or share them via email or social media directly from the app.
6. **Error Handling & Feedback**: Implement robust error handling to notify users about any issues during the translation process and provide suggestions on how to fix them.
7. **Dark Mode Support**: Offer dark mode support to cater to different user preferences and improve usability in various lighting conditions.
8. **Responsive Design**: Ensure the application is fully responsive, working seamlessly across desktops, tablets, and mobile devices.

Your goal is to create an intuitive, powerful tool that not only aids in the translation of Arabic web code but also enhances the overall coding experience for bilingual developers.