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GHSA-vpcf-gvg4-6qwr CVE-2026-27577

n8n: Expression Sandbox Escape Leads to RCE

Critical npm
Severity
9.4 / 10
Critical · CVSS 4.0
Exploit chance (EPSS)
10.72%
Chance of exploitation in the next 30 days. Higher than 95.82% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-94 Improper Control of Generation of Code ('Code Injection')
Fix
1.123.22
Upgrade n8n to this version or later

Description

Impact

Additional exploits in the expression evaluation of n8n have been identified and patched following CVE-2025-68613. An authenticated user with permission to create or modify workflows could abuse crafted expressions in workflow parameters to trigger unintended system command execution on the host running n8n.

Patches

The issues have been fixed in n8n versions 2.10.1, 2.9.3, and 1.123.22. Users should upgrade to one of these versions or later to remediate all known vulnerabilities.

Workarounds

If upgrading is not immediately possible, administrators should consider the following temporary mitigations:

  • Limit workflow creation and editing permissions to fully trusted users only.
  • Deploy n8n in a hardened environment with restricted operating system privileges and network access to reduce the impact of potential exploitation.

These workarounds do not fully remediate the risk and should only be used as short-term mitigation measures.

Resources

Affected versions

npm

PackageVulnerableFixed in
n8n
< 1.123.22
1.123.22
n8n
>= 2.0.0, < 2.9.3
2.9.3
n8n
>= 2.10.0, < 2.10.1
2.10.1
n8n
< 1.123.22
1.123.22
n8n
>= 2.0.0, < 2.9.3
2.9.3
n8n
>= 2.10.0, < 2.10.1
2.10.1

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.

n8n npm → 1.123.22

npm
npm install n8n@1.123.22
yarn
yarn add n8n@1.123.22
pnpm
pnpm add n8n@1.123.22

Severity breakdown

CVSS 4.0 9.4

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

Attack vector
Network
Attack complexity
Low
Attack requirements
None
Privileges required
Low
User interaction
None
Confidentiality (vulnerable system)
High
Integrity (vulnerable system)
High
Availability (vulnerable system)
High
Confidentiality (subsequent systems)
High
Integrity (subsequent systems)
High
Availability (subsequent systems)
High

CVSS 3.1 9.9

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

Attack vector
Network
Attack complexity
Low
Privileges required
Low
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

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-v98v-ff95-f3cp
n8n Vulnerable to Remote Code Execution via Expression Injection
High Known exploited Also affects n8n
GHSA-qgpw-8g46-w95v
n8n: Git Node branch.<name>.remote Config Key Bypasses Sandbox Path Restriction, Enabling Local Git Repository Read
Medium Also affects n8n
GHSA-65xw-2v52-jhxc
n8n: Cross-User Active Workflow ID and Lifecycle Event Disclosure via Missing userId Filter
Medium Also affects n8n
GHSA-pq6c-vh67-xpm3
n8n: Log Streaming Event Destinations Decrypt Generic-Auth Credentials Without Ownership Check
Medium Also affects n8n
GHSA-cqr2-h44g-v75v
n8n: Cross-Tenant Project-Member PII Disclosure via Missing Per-Project Scope Check on Role Assignment Endpoints
Medium Also affects n8n
GHSA-pf83-w3f9-8m37
n8n: Disabled OIDC SSO Endpoints Remain Active and Issue Valid Sessions
Medium Also affects n8n
GHSA-6xcw-7xm6-48c6
n8n: Expression Sandbox Escape via Shared Builtin Tampering and Code-Printer Injection Leads to Code Execution
High Also affects n8n
GHSA-34ff-336r-5q23
n8n: Domain-Restriction Bypass via Unguarded Model-Search Endpoint in OpenAI Chat Model Node
Medium Also affects n8n

Credits: c0rydoras, ediklab, eilonc-pillar, hackerman70000, nil340, zolbooo

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