1bcoder

v0.1.16 suspicious
4.0
Medium Risk

AI coding assistant agent for 1B–7B local models (Ollama, LMStudio, llama.cpp). Terminal REPL with file editing, project map, agents, scripts, and parallel multi-model queries.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks for obfuscation and credential theft but has suspicious metadata which may indicate a lack of proper development practices or potential hidden risks.

  • Low obfuscation risk
  • Low credential risk
  • Suspicious non-HTTPS link in metadata
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: Suspicious non-HTTPS link and low-effort metadata suggest potential risk.

🔬 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

No author email provided

Suspicious Page Links score 2.0

Found 1 suspicious link(s) on the package page

  • Non-HTTPS external link: http://192.168.1.50:11434
Git Repository History

Repository szholobetsky/1bcoder appears legitimate

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 1bcoder
Create a fully-functional mini-application named 'CodeAssist' that leverages the capabilities of the '1bcoder' Python package to enhance developer productivity. This application will serve as a versatile coding assistant, integrating AI-driven suggestions and automation into the development workflow. Here’s a detailed breakdown of the project requirements and features:

1. **Project Initialization**: Start by setting up a Python virtual environment and installing the necessary dependencies, including the '1bcoder' package.
2. **Core Functionality**:
   - **File Editing**: Implement a feature that allows users to edit code files directly from the terminal using '1bcoder'. Users should be able to open, modify, and save files seamlessly.
   - **Project Map**: Develop a project map view that provides an overview of the directory structure and file contents. This will help users navigate their projects more efficiently.
   - **AI Code Suggestions**: Utilize '1bcoder' to integrate AI-driven code suggestions. The application should analyze the context of the code being written and provide relevant suggestions to improve efficiency and reduce errors.
3. **Advanced Features**:
   - **Multi-Model Queries**: Enable users to query multiple local AI models simultaneously to gather diverse insights and suggestions. This will enhance the depth and breadth of assistance provided.
   - **Agent Scripts**: Allow users to create and run custom scripts that interact with the AI models through '1bcoder', automating repetitive tasks and workflows.
4. **User Interface**: Design a user-friendly terminal-based interface for interacting with 'CodeAssist'. Ensure that commands are intuitive and well-documented.
5. **Testing and Documentation**: Thoroughly test the application to ensure reliability and functionality. Provide comprehensive documentation that guides users on how to install, configure, and use 'CodeAssist'.

By utilizing the '1bcoder' package effectively, 'CodeAssist' aims to streamline the development process, making it faster and more efficient for developers.