CVE-2025-2254
June 12, 2025, 4:06 p.m.
8.7
High
Description
An issue has been discovered in GitLab CE/EE affecting all versions from 17.9 before 17.10.8, 17.11 before 17.11.4, and 18.0 before 18.0.2. Improper output encoding in the snipper viewer functionality lead to Cross-Site scripting attacks.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Gitlab |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.
*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 | gitlab | gitlab_ce | 17.9-* | / | / | / | / | / | / | |
| a | gitlab | gitlab_ce | <17.10.8 | / | / | / | / | / | / | |
| a | gitlab | gitlab_ce | <17.11 | / | / | / | / | / | / | |
| a | gitlab | gitlab_ce | <18.0.2 | / | / | / | / | / | / | |
| a | gitlab | gitlab_ee | 17.9-* | / | / | / | / | / | / | |
| a | gitlab | gitlab_ee | <17.10.8 | / | / | / | / | / | / | |
| a | gitlab | gitlab_ee | <17.11 | / | / | / | / | / | / | |
| a | gitlab | gitlab_ee | <18.0.2 | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: LOW
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: NONE
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:N
Timeline
Published: June 12, 2025, 10:16 a.m.
Last Modified: June 12, 2025, 4:06 p.m.
Last Modified: June 12, 2025, 4:06 p.m.
Status : Awaiting Analysis
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
cve@gitlab.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.