CVE-2025-43858
April 24, 2025, 7:15 p.m.
9.2
Critical
Description
YoutubeDLSharp is a wrapper for the command-line video downloaders youtube-dl and yt-dlp. In versions starting from 1.0.0-beta4 and prior to 1.1.2, an unsafe conversion of arguments allows the injection of a malicious commands when starting `yt-dlp` from a commands prompt running on Windows OS with the `UseWindowsEncodingWorkaround` value defined to true (default behavior). If a user is using built-in methods from the YoutubeDL.cs file, the value is true by default and a user cannot disable it from these methods. This issue has been patched in version 1.1.2.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Youtubedlsharp |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-77
Improper Neutralization of Special Elements used in a Command ('Command Injection')
The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended 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 | youtubedlsharp | yt-dlp | 1.0.0-beta4-1.1.2 | / | / | / | / | / | / | / |
References
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: LOCAL
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: CHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: LOW
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:L
Timeline
Published: April 24, 2025, 6:15 p.m.
Last Modified: April 24, 2025, 7:15 p.m.
Last Modified: April 24, 2025, 7:15 p.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.