GHSA-5xrp-6693-jjx9 CVE-2026-1470
n8n Unsafe Workflow Expression Evaluation Allows Remote Code Execution
- Severity
- 9.9 / 10
- Critical · CVSS 3.1
- Exploit chance (EPSS)
- 20.40%
- Chance of exploitation in the next 30 days. Higher than 97.49% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-95 Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')
- Fix
1.123.17- Upgrade n8n to this version or later
Description
n8n contains a critical Remote Code Execution (RCE) vulnerability in its workflow Expression evaluation system. Expressions supplied by authenticated users during workflow configuration may be evaluated in an execution context that is not sufficiently isolated from the underlying runtime.
An authenticated attacker could abuse this behavior to execute arbitrary code with the privileges of the n8n process. Successful exploitation may lead to full compromise of the affected instance, including unauthorized access to sensitive data, modification of workflows, and execution of system-level operations.
Affected versions
npm
| Package | Vulnerable | Fixed in |
|---|---|---|
| n8n | < 1.123.17 |
1.123.17 |
| n8n | >= 2.0.0, < 2.4.5 |
2.4.5 |
| n8n | >= 2.5.0, < 2.5.1 |
2.5.1 |
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 → 1.123.17
- npm
npm install n8n@1.123.17- yarn
yarn add n8n@1.123.17- pnpm
pnpm add n8n@1.123.17
Severity breakdown
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-95: Improper Neutralization of Directives in Dynamically Evaluated Code ('Eval Injection')
The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes code syntax before using the input in a dynamic evaluation call (e.g. "eval").
How to prevent it
- Architecture and Design, Implementation: If possible, refactor your code so that it does not need to use eval() at all.
- 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.
- Implementation: Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180, CWE-181). Make sure that your application does not inadvertently decode the same input twice (CWE-174). Such errors could be used to bypass allowlist schemes by introducing dangerous inputs after they have been checked. Use libraries such as the OWASP ESAPI Canonicalization control. Consider performing repeated canonicalization until your input does not change any more. This will avoid double-decoding and similar scenarios, but it might inadvertently modify inputs that are allowed to contain properly-encoded dangerous content.
- 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
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why 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 |
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