AI Analysis
The package shows signs of potential misuse due to shell execution capabilities, though the lack of obfuscation and credential harvesting reduces immediate concerns. The maintainer's metadata is incomplete, adding a layer of uncertainty.
- Shell risk due to subprocess usage
- Incomplete maintainer metadata
Per-check LLM notes
- Network: The use of urllib and httpx suggests the package may be performing network requests, which could be benign if it's part of its intended functionality.
- Shell: The execution of commands via subprocess indicates potential risks as it can be misused to execute arbitrary commands on the user's system.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer's author name is missing and they appear to be new or inactive, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (4.6/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (27895 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
467 type-annotated function signatures detected in source
Limited contributor diversity
1 unique contributor(s) across 100 commits in estevaofon/aruSingle author but highly active (100 commits)
Heuristic Checks
Found 4 network call pattern(s)
a).encode("ascii") req = urllib.request.Request( url, data=body, method=") try: with urllib.request.urlopen(req, timeout=timeout) as resp: raw = ret httpx with httpx.Client(timeout=URL_FETCH_TIMEOUT, follow_redirects=True) as client:th() async_http_client = httpx.AsyncClient( auth=auth, timeout=httpx.Timeout(120.0, c
No obfuscation patterns detected
Found 6 shell execution pattern(s)
try: process = subprocess.Popen( command, shell=True,) -> None: try: subprocess.run( ["git", "--version"], capture_outstr(target)]) result = subprocess.run(cmd, capture_output=True, text=True, timeout=120) if regit_available() result = subprocess.run( ["git", "-C", str(target), "pull", "--ff-only"],self._cached_git_status = subprocess.run( ["git", "status", "-s"], capture_output=Trcommand, shell=True, stdout=subprocess.PIPE, stderr=s
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Repository estevaofon/aru appears legitimate
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully functional code playground mini-app using the 'aru-code' package, which is a clone of Claude Code built with Agno agents. This app will allow users to write, run, and share simple code snippets in various programming languages directly within their browser. Here are the steps and features you need to implement: 1. **Setup**: Start by installing the 'aru-code' package and setting up your development environment. Ensure you have Python installed and create a virtual environment for this project. 2. **User Interface**: Design a clean and user-friendly interface where users can input their code. Include syntax highlighting and line numbering for better readability. 3. **Code Execution**: Implement a feature that allows users to execute their code snippets. Use the 'aru-code' package to manage the execution process, ensuring it supports multiple programming languages like Python, JavaScript, and Ruby. 4. **Output Display**: After execution, display the output of the code in a separate section of the UI. Handle errors gracefully and provide meaningful error messages. 5. **Sharing Feature**: Allow users to save and share their code snippets. They should be able to generate a unique URL that others can use to view and run the same code. 6. **Dark Mode Toggle**: Add a toggle option for dark mode to cater to different user preferences. 7. **Language Selector**: Provide a dropdown menu to select the language for the code snippet before execution. 8. **Documentation**: Write a README file explaining how to install, use, and contribute to the project. Include examples of how to use the app effectively. Utilize the 'aru-code' package throughout the development process, leveraging its capabilities to streamline the code execution and management functionalities. Ensure the final product is robust, scalable, and easy to use.
💬 Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue