autobyteus

v1.4.4 suspicious
3.0
Low Risk

Multi-Agent framework

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network calls, shell execution, and obfuscation. However, the missing author's name and apparent inactivity raise concerns about the package's legitimacy.

  • Missing author's name
  • Author appears to be inactive
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author's name is missing and they appear to be inactive, raising some suspicion but not definitive proof of malintent.

📦 Package Quality Overall: Low (4.8/10)

◈ 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 (11525 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

  • 103 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in AutoByteus/autobyteus
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

⚠ Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://`
✓ Git Repository History

Repository AutoByteus/autobyteus 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 autobyteus 
Your task is to create a fully-functional mini-application that simulates a multi-agent system for managing a virtual library. This application will use the 'autobyteus' Python package, which provides a framework for building and managing multi-agent systems. Here’s a detailed breakdown of the project requirements and steps to follow:

1. **Project Overview**: Design a system where multiple agents collaborate to manage books in a virtual library. Agents will handle tasks such as cataloging new books, updating book statuses (e.g., borrowed, returned), and assisting users in finding books.

2. **Core Features**:
   - **Agent Roles**: Define different roles for agents (e.g., Cataloger, Librarian, SearchAgent).
   - **Book Management**: Implement functionalities for adding, removing, and updating books in the library database.
   - **User Interaction**: Allow users to search for books, request information about specific books, and check book availability.
   - **Status Updates**: Keep track of book statuses (available, borrowed) and notify users accordingly.

3. **Using 'autobyteus'**:
   - Initialize your multi-agent system using 'autobyteus'.
   - Configure each agent according to its role.
   - Use 'autobyteus' communication protocols to ensure seamless interaction between agents.
   - Leverage 'autobyteus' event handling mechanisms to manage user requests and agent responses efficiently.

4. **Development Steps**:
   - Step 1: Set up your development environment and install 'autobyteus'.
   - Step 2: Define the architecture of your multi-agent system.
   - Step 3: Implement each agent's logic based on their assigned roles.
   - Step 4: Integrate user interaction capabilities.
   - Step 5: Test the system with various scenarios to ensure reliability and efficiency.

5. **Additional Enhancements**:
   - Consider implementing a graphical user interface (GUI) for better user experience.
   - Explore adding machine learning capabilities to predict popular books or recommend books to users.

6. **Deliverables**:
   - A fully functional mini-application.
   - Documentation explaining how the application works and how it leverages 'autobyteus'.
   - A report detailing any challenges faced during development and how they were overcome.

This project aims to showcase the power and flexibility of the 'autobyteus' package while providing a practical solution for managing a virtual library.

💬 Discussion Feed

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