agentrix-core

v0.2.6 suspicious
5.0
Medium Risk

Agentrix agent runtime: surface-agnostic, production-grade coding agent.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows signs of potential credential harvesting and poor metadata quality, raising concerns about its legitimacy and intentions.

  • High credential risk due to accessing passwords
  • Low metadata quality and new maintainer account
Per-check LLM notes
  • Network: The use of httpx.AsyncClient with proxies might indicate external communications but without additional context, it's hard to determine if it's malicious.
  • Shell: No shell execution patterns detected, which is normal and expected.
  • Obfuscation: The use of pickle.loads suggests potential for code execution from untrusted sources, but it may also be used for legitimate purposes like serializing and deserializing objects.
  • Credentials: Accessing passwords via keyring.get_password indicates the package might be harvesting credentials, which is a high-risk behavior unless explicitly documented as necessary functionality.
  • Metadata: The maintainer has a new or inactive PyPI account and lacks PyPI classifiers, indicating potential low effort or poor metadata quality.

📦 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 (1679 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

  • 270 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 1.5

Found 1 network call pattern(s)

  • s of these # packages call ``httpx.AsyncClient(proxies=...)`` internally, which crashes # under ``httpx>=0
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • r: vec = pickle.loads(row[5]) score = _cosine(qvec, vec)
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 2.5

Found 1 credential access pattern(s)

  • try: val = keyring.get_password(settings.secrets_service, name) if val:
✓ 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 4.0

2 maintainer concern(s) found

  • Author "Agentrix" 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 agentrix-core 
Create a fully-functional mini-app called 'CodeCraft' that leverages the 'agentrix-core' Python package to enable users to write, test, and deploy simple scripts or functions in a browser-based interface. The app should be designed for both beginners and intermediate coders who want to learn about scripting and automation without needing to install any software on their local machines.

### Features:
1. **User Authentication:** Users should be able to sign up, log in, and manage their profiles.
2. **Script Editor:** A code editor where users can write Python scripts. The editor should have basic syntax highlighting and auto-completion features.
3. **Interactive Console:** Users should be able to run their scripts directly from the editor and see the output in an interactive console below the editor.
4. **Script Repository:** A feature that allows users to save their scripts and access them later. They should also be able to share their scripts with others.
5. **Testing Environment:** A sandboxed environment where users can test their scripts before deploying them. This environment should simulate real-world conditions as closely as possible.
6. **Deployment Option:** Once tested, users should be able to deploy their scripts using 'agentrix-core'. Deployed scripts should be accessible via a unique URL.
7. **Feedback System:** A system where users can provide feedback on deployed scripts, which can help other users improve their own scripts.
8. **Documentation:** Comprehensive documentation for users explaining how to use the various features of the app, including how 'agentrix-core' works under the hood.

### Utilization of 'agentrix-core':
- Use 'agentrix-core' to handle the backend logic for script execution and deployment. Specifically, leverage its production-grade coding agent capabilities to ensure that scripts are run in a secure, efficient manner.
- Implement 'agentrix-core' to facilitate the deployment process, ensuring that scripts are packaged and deployed correctly across different environments.
- Integrate 'agentrix-core' to monitor the performance of deployed scripts and provide real-time analytics back to the user interface.

### Step-by-Step Guide:
1. Set up a Flask or Django backend server to handle HTTP requests and responses.
2. Implement user authentication using JWT tokens for secure sessions.
3. Develop a React or Vue.js frontend that communicates with the backend API.
4. Integrate 'agentrix-core' into your backend to manage script execution and deployment processes.
5. Design the interactive console and repository features, allowing users to interact with their scripts easily.
6. Test the entire system thoroughly, focusing on security and performance.
7. Launch the app and gather user feedback to iterate and improve.