CVE-2024-47600
Dec. 18, 2024, 9:43 p.m.
9.1
Critical
Description
GStreamer is a library for constructing graphs of media-handling components. An OOB-read vulnerability has been detected in the format_channel_mask function in gst-discoverer.c. The vulnerability affects the local array position, which is defined with a fixed size of 64 elements. However, the function gst_discoverer_audio_info_get_channels may return a guint channels value greater than 64. This causes the for loop to attempt access beyond the bounds of the position array, resulting in an OOB-read when an index greater than 63 is used. This vulnerability can result in reading unintended bytes from the stack. Additionally, the dereference of value->value_nick after the OOB-read can lead to further memory corruption or undefined behavior. This vulnerability is fixed in 1.24.10.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Gstreamer Project |
|
|
Weaknesses
Common security weaknesses mapped to this vulnerability.
CWE-125
Out-of-bounds Read
The product reads data past the end, or before the beginning, of the intended buffer.
*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 | gstreamer_project | gstreamer | / | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: NONE
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:H
Timeline
Published: Dec. 12, 2024, 2:03 a.m.
Last Modified: Dec. 18, 2024, 9:43 p.m.
Last Modified: Dec. 18, 2024, 9:43 p.m.
Status : Analyzed
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.