@lobehub/lobehub@2.1.21

LobeHub - an open-source,comprehensive AI Agent framework that supports speech synthesis, multimodal, and extensible Function Call plugin system. Supports one-click free deployment of your private ChatGPT/LLM web application.

  • latest version

    2.1.26

  • first published

    7 months ago

  • latest version published

    3 months ago

  • licenses detected

  • Direct Vulnerabilities

    Known vulnerabilities in the @lobehub/lobehub package. This does not include vulnerabilities belonging to this package’s dependencies.

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    VulnerabilityVulnerable Version
    • M
    Command Injection

    @lobehub/lobehub is a LobeHub - an open-source,comprehensive AI Agent framework that supports speech synthesis, multimodal, and extensible Function Call plugin system. Supports one-click free deployment of your private ChatGPT/LLM web application.

    Affected versions of this package are vulnerable to Command Injection in the message rendering process when handling custom tags in the Renderer component. An attacker can execute arbitrary system commands with the privileges of the current user by inducing the application to process malicious content that triggers the exposed runCommand IPC interface via a crafted LLM provider endpoint.

    How to fix Command Injection?

    A fix was pushed into the master branch but not yet published.

    >=0.0.0
    • M
    User Impersonation

    @lobehub/lobehub is a LobeHub - an open-source,comprehensive AI Agent framework that supports speech synthesis, multimodal, and extensible Function Call plugin system. Supports one-click free deployment of your private ChatGPT/LLM web application.

    Affected versions of this package are vulnerable to User Impersonation via the X-lobe-chat-auth header on webapi routes. An attacker can gain unauthorized access to protected API endpoints and perform actions as an authenticated user by crafting a forged header using a hardcoded XOR key to bypass authentication checks. This allows access to sensitive operations, including impersonating users and utilizing backend model provider credentials.

    How to fix User Impersonation?

    A fix was pushed into the master branch but not yet published.

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