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n8n has SQL Injection in Snowflake and MySQL Nodes

Moderate severity GitHub Reviewed Published Apr 22, 2026 in n8n-io/n8n • Updated Apr 29, 2026

Package

npm n8n (npm)

Affected versions

< 1.123.32
>= 2.18.0, < 2.18.1
>= 2.0.0, < 2.17.4

Patched versions

1.123.32
2.18.1
2.17.4

Description

Impact

The fix for GHSA-f3f2-mcxc-pwjx did not cover the Snowflake node or the legacy MySQL v1 node. Both nodes construct SQL queries by directly interpolating user-controlled table names, column names, and update keys into query strings without identifier escaping, enabling SQL injection against the connected database.

Exploitation requires a specific workflow configuration:

  • The Snowflake or MySQL v1 node must be used with user-controlled input passed via expressions (e.g., from a form or webhook) into identifier fields such as table name, column name, or update key.

Successful exploitation could allow data exfiltration, modification, or deletion on the downstream database.

Patches

The issue has been fixed in n8n versions 1.123.32, 2.17.4, and 2.18.1. Users should upgrade to one of these versions or later to remediate the vulnerability.

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.
  • Migrate workflows from the legacy MySQL v1 node to the MySQL v2 node, which already implements identifier escaping.
  • Disable the Snowflake node by adding n8n-nodes-base.snowflake to the NODES_EXCLUDE environment variable.
  • Avoid passing unvalidated external user input into table name, column name, or update key fields via expressions in the affected nodes.

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

References

@Jubke Jubke published to n8n-io/n8n Apr 22, 2026
Published to the GitHub Advisory Database Apr 29, 2026
Reviewed Apr 29, 2026
Last updated Apr 29, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability None
Subsequent System Impact Metrics
Confidentiality High
Integrity High
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:N/SC:H/SI:H/SA:N

EPSS score

Weaknesses

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data. Learn more on MITRE.

CVE ID

CVE-2026-42237

GHSA ID

GHSA-hp3c-vfpm-q4f7

Source code

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