CVE-2026-48547

June 11, 2026, 8:57 p.m.

8.5
High

Description

KanaDojo contains a command injection vulnerability that allows an attacker with pull request access to execute arbitrary shell commands by inserting shell metacharacters into the version or changes fields of patchNotesData.json, which are interpolated unsanitized into a child_process.execSync() call in the release.yml workflow. Attackers can have a malicious pull request merged to trigger the GitHub Actions runner with contents write permissions and access to GITHUB_TOKEN.

Product(s) Impacted

Vendor Product Versions
Kanadojo
  • Kanadojo
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-78
Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
The product constructs all or part of an OS command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended OS 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 kanadojo kanadojo / / / / / / / /

CVSS Score

8.5 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: June 11, 2026, 7:16 p.m.
Last Modified: June 11, 2026, 8:57 p.m.

Status : Deferred

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

More info

*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.