GHSA-3gcm-f6qx-ff7p CVE-2025-59528
Flowise has Remote Code Execution vulnerability
- Severity
- 10.0 / 10
- Critical · CVSS 3.1
- Exploit chance (EPSS)
- 86.49%
- Chance of exploitation in the next 30 days. Higher than 99.74% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-94 Improper Control of Generation of Code ('Code Injection')
- Fix
3.0.6- Upgrade flowise to this version or later
Description
Description
Cause of the Vulnerability
The CustomMCP node allows users to input configuration settings for connecting to an external MCP (Model Context Protocol) server. This node parses the user-provided mcpServerConfig string to build the MCP server configuration. However, during this process, it executes JavaScript code without any security validation.
Specifically, inside the convertToValidJSONString function, user input is directly passed to the Function() constructor, which evaluates and executes the input as JavaScript code. Since this runs with full Node.js runtime privileges, it can access dangerous modules such as child_process and fs.
Vulnerability Flow
- User Input Received: Input is provided via the API endpoint
/api/v1/node-load-method/customMCPthrough themcpServerConfigparameter. - Variable Substitution: The
substituteVariablesInStringfunction replaces template variables like$vars.xxx, but no security filtering is applied during this step. - Dangerous Code Execution: The
convertToValidJSONStringfunction executes the input usingFunction('return ' + inputString)(). If theinputStringcontains malicious code, it gets executed in the global Node.js context, allowing actions such as command execution and file system access.
Taint Flow
-
Taint 01: Route Registration
index.ts(Line 5) -
Taint 02: Controller
index.ts(Line 57–78) -
Taint 03: Service
index.ts(Line 91–94) -
Taint 04: CustomMCP Node Entry Point
CustomMCP.ts(Line 132) -
Taint 05: Variable Substitution
CustomMCP.ts(Line 220) -
Taint 06: Dangerous Constructor Execution
CustomMCP.ts(Line 262–270)
Proof of Concept (PoC)
curl -X POST http://localhost:3000/api/v1/node-load-method/customMCP \
-H "Content-Type: application/json" \
-H "Authorization: Bearer tmY1fIjgqZ6-nWUuZ9G7VzDtlsOiSZlDZjFSxZrDd0Q" \
-d '{
"loadMethod": "listActions",
"inputs": {
"mcpServerConfig": "({x:(function(){const cp = process.mainModule.require(\"child_process\");cp.execSync(\"echo !!RCE-OK!! >/tmp/RCE.txt\");return 1;})()})"
}
}'
<img width="1907" height="958" alt="image" src="https://github.com/user-attachments/assets/78b50eb1-67af-4c8b-97ea-7e2c05426962" />
When executed, this creates a file /tmp/RCE.txt on the server, confirming command execution.
Impact
Complete System Takeover and Infrastructure Threat
This vulnerability allows attackers to execute arbitrary JavaScript code on the Flowise server, leading to:
- Full system compromise
- File system access
- Command execution
- Sensitive data exfiltration
As only an API token is required, this poses an extreme security risk to business continuity and customer data.
Affected versions
npm
| Package | Vulnerable | Fixed in |
|---|---|---|
| flowise | >= 3.0.5, < 3.0.6 |
3.0.6 |
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 → 3.0.6
- npm
npm install flowise@3.0.6- yarn
yarn add flowise@3.0.6- pnpm
pnpm add flowise@3.0.6
Severity breakdown
CVSS 3.1 10.0
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- None
- User interaction
- None
- Scope
- Changed
- Confidentiality
- High
- Integrity
- High
- Availability
- High
Weakness
CWE-94: Improper Control of Generation of Code ('Code Injection')
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.
How to prevent it
- Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
- Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
- Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
- Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].
References
Advisories
Packages
Other links
- github.com/FlowiseAI/Flowise/security/advisories/GHSA-3gcm-f6qx-ff7p
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/pack…
- github.com/FlowiseAI/Flowise/releases/tag/flowise%403.0.6
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-w7x8-q2gp-5cgg Flowise Prompt Injection to RCE and SSRF via CSV/Airtable Agent Python Validator Bypass | Critical | Also affects flowise |
| GHSA-9gvv-qjj3-2p6g Flowise NodeVM sandbox escape via puppeteer allowlist - authenticated RCE and arbitrary file read via Chromium | High | Also affects flowise |
| GHSA-qgvm-j2hm-6m38 Flowise: Unauthenticated OAuth2 token refresh endpoint returns access tokens — enables token theft for any connected service | Critical | Also affects flowise |
| GHSA-5xvg-pmgg-3mxr Flowise: CSV Agent Prompt Injection Remote Code Execution Vulnerability | Critical | Also affects flowise |
| 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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