axion-code

v1.0.1 suspicious
4.0
Medium Risk

Axion Code - Python AI coding assistant CLI

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risk due to its use of potentially obfuscated code, interaction with shell commands, and incomplete maintainer metadata. These factors collectively warrant further scrutiny.

  • obfuscation risk
  • shell execution risk
  • incomplete maintainer metadata
Per-check LLM notes
  • Network: The network calls suggest the package uses an HTTP client for API interactions which is common but should be reviewed for unexpected endpoints or excessive data transfer.
  • Shell: The shell execution patterns indicate the package interacts with git commands which might be for version control or similar legitimate purposes but could also signify unintended behavior.
  • Obfuscation: The code shows signs of obfuscation through compression and base64 encoding, which could be used for malicious purposes but might also be legitimate.
  • Credentials: No clear patterns indicating credential harvesting were detected.
  • Metadata: The maintainer has an incomplete profile and appears to be new or inactive, which may indicate potential risk.

📦 Package Quality Overall: Medium (5.4/10)

◈ 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 (27637 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 532 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 83 commits in cypher125/Axion-Code
  • Single author but highly active (83 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 9.0

Found 6 network call pattern(s)

  • e: self._client = httpx.AsyncClient( base_url=self.base_url, tim
  • = model self._http = httpx.AsyncClient(timeout=httpx.Timeout(300.0)) @classmethod def from
  • -> None: self._http = httpx.AsyncClient(timeout=httpx.Timeout(120.0)) self._api_key = api_ke
  • -> None: self._http = httpx.AsyncClient(timeout=httpx.Timeout(300.0, connect=30.0)) self._ap
  • import httpx resp = httpx.get("http://localhost:11434/api/tags", timeout=2.0) if r
  • state, } async with httpx.AsyncClient(timeout=30.0) as client: response = await client.pos
⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • d decompress compressed = base64.b64decode(shared.data) session_json = zlib.decompress(compressed).
  • eps: try: __import__(dep) lines.append(f" {dep}: OK") except Imp
  • ared.data) session_json = zlib.decompress(compressed).decode("utf-8") session_dict = json.loads(se
⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • """ try: result = subprocess.run( ["git", "rev-parse", "--abbrev-ref", "HEAD"],
  • """ try: result = subprocess.run( ["git", "status", "--short"], captu
  • try: result = subprocess.run( git_args, capture_output=True, text=True, t
  • Git try: result = subprocess.run( ["git", "--version"], capture_output=True, text
  • """ try: result = subprocess.run( ["git"] + args, capture_output=True
  • try: result = subprocess.run( cmd, shell=True,
✓ 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

Repository cypher125/Axion-Code appears legitimate

⚠ 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 axion-code 
Create a fully-functional mini-application named 'CodeMentor' that serves as an intelligent coding assistant for developers using the 'axion-code' package. This application should allow users to input a piece of code along with a specific problem they're facing, and it will provide suggestions, improvements, and potential solutions. Here’s how you can structure the application:

1. **Setup**: Start by installing the 'axion-code' package and setting up your Python environment.
2. **User Interface**: Design a simple command-line interface (CLI) where users can input their code snippet and the issue they are encountering.
3. **Code Analysis**: Utilize 'axion-code' to analyze the provided code snippet and identify potential issues, inefficiencies, or areas for improvement.
4. **Feedback Generation**: Based on the analysis, generate feedback that includes suggested improvements, alternative approaches, and best practices.
5. **Integration Suggestions**: Offer integration suggestions with other popular Python packages or libraries that could enhance the functionality or performance of the code.
6. **Documentation Links**: Provide links to relevant documentation or tutorials that could help users understand the suggested changes better.
7. **Testing**: Implement a basic testing mechanism within the application to demonstrate the impact of applying the suggested changes to the original code snippet.
8. **User Interaction**: Allow users to interactively choose which suggestions they want to apply to their code and see real-time changes and improvements.
9. **Logging**: Keep logs of all interactions and feedback provided for future reference and learning purposes.

Ensure the application is user-friendly, provides clear and concise feedback, and leverages the full capabilities of the 'axion-code' package to offer valuable insights and improvements to the user's code.

💬 Discussion Feed

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