astromesh

v0.28.5 suspicious
4.0
Medium Risk

Astromesh Agent Runtime Platform — multi-model, multi-pattern AI agent runtime

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate network activity that requires further scrutiny and shows signs of possible obfuscation and low maintenance efforts, raising concerns about its legitimacy and security posture.

  • moderate network interaction
  • potential obfuscation
  • low maintenance
Per-check LLM notes
  • Network: The use of asynchronous HTTP requests may indicate legitimate network interaction but requires further investigation to confirm its purpose and legitimacy.
  • Shell: No shell execution patterns detected, suggesting low risk of direct system command execution.
  • Obfuscation: The observed patterns may indicate some level of obfuscation, but they do not clearly suggest malicious intent as they could be part of normal error handling and model evaluation processes.
  • Credentials: No clear signs of credential harvesting were detected.
  • Metadata: The package shows low maintenance and effort, which could indicate potential risk.

📦 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 (19819 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

  • 176 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 6.0

Found 4 network call pattern(s)

  • } async with httpx.AsyncClient() as client: resp = await client.post(url, json=
  • s_token}"} async with httpx.AsyncClient() as client: # Step 1: Get the download URL.
  • ._http_client = ( httpx.AsyncClient(timeout=30.0) if self._transport in ("sse", "http") else Non
  • rState() self._http = httpx.AsyncClient(timeout=10.0) self._left = False self.node_
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • (info.path) model.eval() return model except ImportError:
  • vice) self._model.eval() except ImportError: raise RuntimeError
✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ 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 6.0

3 maintainer concern(s) found

  • 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 astromesh 
Create a Python-based mini-application called 'Astromesh Explorer' that leverages the Astromesh package to showcase its capabilities in managing and executing AI agents across different models and patterns. This application will serve as a user-friendly interface for experimenting with various AI functionalities without needing deep technical knowledge of AI model architectures.

**Core Functionality:**
1. **Agent Management Interface:** Develop a graphical user interface (GUI) using a library like PyQt or Tkinter to allow users to manage their AI agents. Users should be able to create new agents, configure settings, and deploy them.
2. **Model and Pattern Selection:** Integrate Astromesh's ability to support multiple AI models and execution patterns. Provide a feature within the GUI where users can select from a list of available models (e.g., TensorFlow, PyTorch) and patterns (e.g., sequential, parallel).
3. **Real-Time Monitoring:** Implement real-time monitoring of the deployed agents. Display metrics such as processing speed, accuracy, and resource usage directly on the GUI.
4. **Customization Options:** Allow users to customize the behavior of their agents by adjusting parameters and input data through the GUI.
5. **Documentation and Help:** Include comprehensive documentation and a help section within the application that explains how to use each feature and provides examples.

**Steps to Utilize Astromesh Package:**
- Import the necessary modules from Astromesh at the beginning of your Python scripts.
- Use Astromesh’s API to initialize the agent runtime environment.
- For each agent creation, utilize Astromesh's functions to specify the model and pattern, set up configurations, and start the agent.
- Leverage Astromesh's monitoring tools to gather performance data and update the GUI with real-time information.
- Ensure all interactions with Astromesh are encapsulated within the application logic to maintain a clean and modular codebase.

💬 Discussion Feed

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