aurexcode2

v0.1.1 suspicious
4.0
Medium Risk

Aurex — Terminal AI Coding Agent powered by NVIDIA NIM

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is flagged as suspicious due to its moderate network and metadata risks, indicating potential vulnerabilities and lack of trustworthiness.

  • moderate network risk
  • low metadata quality
Per-check LLM notes
  • Network: The package makes network calls to an external server, which could potentially be used for data exfiltration or command and control communications.
  • Shell: Use of os.system and subprocess.run with shell=True can indicate potential execution of arbitrary commands, which might be exploited for malicious purposes.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows signs of low maintenance and potential lack of trustworthiness due to missing author details and a single version release.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (2288 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

  • 21 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 score 3.0

Found 2 network call pattern(s)

  • 6, }).encode() req = urllib.request.Request( f"{config.BASE_URL}/chat/completions",
  • ethod="POST", ) with urllib.request.urlopen(req, timeout=120) as resp: for raw in resp:
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 8.0

Found 4 shell execution pattern(s)

  • ──── def main() -> None: os.system("clear" if os.name == "posix" else "cls") ui.print_banne
  • t.clear_history() os.system("clear" if os.name == "posix" else "cls") ui.pri
  • tr: try: result = subprocess.run( command, shell=True, capture_output=True, text=
  • ess.run( command, shell=True, capture_output=True, text=True, timeout=60 )
✓ 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 aurexcode2 
Create a terminal-based code generation assistant named 'CodeGenX' using the Python package 'aurexcode2'. This assistant will leverage the power of NVIDIA NIM to generate high-quality Python code snippets based on user prompts. Your task is to design and implement a fully functional mini-application that allows developers to interact with 'CodeGenX' through a command-line interface (CLI). Here’s a detailed guide on how to approach this project:

1. **Setup Project Environment**: Begin by setting up your development environment. Ensure you have Python installed along with the necessary packages including 'aurexcode2'. Use pip to install 'aurexcode2' if it's not already available.

2. **Design CLI Interface**: Design a simple yet effective CLI where users can input their coding requirements or queries. The interface should support basic commands such as 'generate', 'help', and 'exit'.

3. **Integrate 'aurexcode2'**: Utilize the 'aurexcode2' package to process user inputs and generate appropriate Python code snippets. Make sure to handle various types of requests, such as generating functions, classes, or even entire modules based on user specifications.

4. **Enhance User Experience**: Implement features like auto-suggestions for common coding tasks, error handling for invalid inputs, and the ability to save generated code snippets to a specified file location.

5. **Testing and Validation**: Test your application thoroughly to ensure it works as expected across different scenarios. Validate the generated code snippets for correctness and efficiency.

6. **Documentation**: Finally, document your application clearly, providing instructions on how to set it up, use its functionalities, and troubleshoot any issues that may arise.

This project aims to showcase the capabilities of 'aurexcode2' in enhancing developer productivity through intelligent code generation.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!