CVE-2025-53095
July 1, 2025, 2:15 a.m.
9.6
Critical
Description
Sunshine is a self-hosted game stream host for Moonlight. Prior to version 2025.628.4510, the web UI of Sunshine lacks protection against Cross-Site Request Forgery (CSRF) attacks. This vulnerability allows an attacker to craft a malicious web page that, when visited by an authenticated user, can trigger unintended actions within the Sunshine application on behalf of that user. Specifically, since the application does OS command execution by design, this issue can be exploited to abuse the "Command Preparations" feature, enabling an attacker to inject arbitrary commands that will be executed with Administrator privileges when an application is launched. This issue has been patched in version 2025.628.4510.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Sunshine |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-352
Cross-Site Request Forgery (CSRF)
The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request.
*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 | sunshine | game_stream_host | <2025.628.4510 | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
Timeline
Published: July 1, 2025, 2:15 a.m.
Last Modified: July 1, 2025, 2:15 a.m.
Last Modified: July 1, 2025, 2:15 a.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
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.