CVE-2024-11828
Dec. 12, 2024, 9:07 p.m.
4.3
Medium
Description
A denial of service (DoS) condition was discovered in GitLab CE/EE affecting all versions from 13.2.4 before 17.4.5, 17.5 before 17.5.3, and 17.6 before 17.6.1. By leveraging this vulnerability an attacker could create a DoS condition by sending crafted API calls. This was a regression of an earlier patch.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Gitlab |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-407
Inefficient Algorithmic Complexity
An algorithm in a product has an inefficient worst-case computational complexity that may be detrimental to system performance and can be triggered by an attacker, typically using crafted manipulations that ensure that the worst case is being reached.
*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 | / | / | / | / | community | / | / | / |
| a | gitlab | gitlab | / | / | / | / | enterprise | / | / | / |
| a | gitlab | gitlab | / | / | / | / | community | / | / | / |
| a | gitlab | gitlab | / | / | / | / | enterprise | / | / | / |
| a | gitlab | gitlab | 17.6.0 | / | / | / | community | / | / | / |
| a | gitlab | gitlab | 17.6.0 | / | / | / | enterprise | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: LOW
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: NONE
- Availability Impact: LOW
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
Timeline
Published: Nov. 26, 2024, 7:15 p.m.
Last Modified: Dec. 12, 2024, 9:07 p.m.
Last Modified: Dec. 12, 2024, 9:07 p.m.
Status : Analyzed
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.