CVE-2025-66404

Dec. 4, 2025, 5:15 p.m.

6.4
Medium

Description

MCP Server Kubernetes is an MCP Server that can connect to a Kubernetes cluster and manage it. Prior to 2.9.8, there is a security issue exists in the exec_in_pod tool of the mcp-server-kubernetes MCP Server. The tool accepts user-provided commands in both array and string formats. When a string format is provided, it is passed directly to shell interpretation (sh -c) without input validation, allowing shell metacharacters to be interpreted. This vulnerability can be exploited through direct command injection or indirect prompt injection attacks, where AI agents may execute commands without explicit user intent. This vulnerability is fixed in 2.9.8.

Product(s) Impacted

Vendor Product Versions
Mcp
  • Mcp-server-kubernetes
  • <2.9.8

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-77
Improper Neutralization of Special Elements used in a Command ('Command Injection')
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a mcp mcp-server-kubernetes <2.9.8 / / / / / / /

CVSS Score

6.4 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: HIGH
  • Privileges Required: HIGH
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:U/C:H/I:H/A:H

    View Vector String

Timeline

Published: Dec. 3, 2025, 9:15 p.m.
Last Modified: Dec. 4, 2025, 5:15 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.