CVE-2025-66294

Dec. 2, 2025, 5:16 p.m.

8.7
High

Description

Grav is a file-based Web platform. Prior to 1.8.0-beta.27, a Server-Side Template Injection (SSTI) vulnerability exists in Grav that allows authenticated attackers with editor permissions to execute arbitrary commands on the server and, under certain conditions, may also be exploited by unauthenticated attackers. This vulnerability stems from weak regex validation in the cleanDangerousTwig method. This vulnerability is fixed in 1.8.0-beta.27.

Product(s) Impacted

Vendor Product Versions
Grav
  • Grav
  • <1.8.0-beta.27

Weaknesses

Common security weaknesses mapped to this vulnerability.

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.

*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 grav grav <1.8.0-beta.27 / / / / / / /

CVSS Score

8.7 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/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: Dec. 1, 2025, 9:15 p.m.
Last Modified: Dec. 2, 2025, 5:16 p.m.

Status : Undergoing 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.