CVE-2025-12343
Ffmpeg: double-free vulnerability in ffmpeg tensorflow dnn backend
Description
A flaw was found in FFmpeg’s TensorFlow backend within the libavfilter/dnn_backend_tf.c source file. The issue occurs in the dnn_execute_model_tf() function, where a task object is freed multiple times in certain error-handling paths. This redundant memory deallocation can lead to a double-free condition, potentially causing FFmpeg or any application using it to crash when processing TensorFlow-based DNN models. This results in a denial-of-service scenario but does not allow arbitrary code execution under normal conditions.
INFO
Published Date :
Feb. 18, 2026, 9:16 p.m.
Last Modified :
Feb. 18, 2026, 9:16 p.m.
Remotely Exploit :
No
Source :
[email protected]
CVSS Scores
| Score | Version | Severity | Vector | Exploitability Score | Impact Score | Source |
|---|---|---|---|---|---|---|
| CVSS 3.1 | LOW | 92fb86c3-55a5-4fb5-9c3f-4757b9e96dc5 | ||||
| CVSS 3.1 | LOW | [email protected] |
Solution
- Review and correct memory management in dnn_execute_model_tf function.
- Ensure task objects are freed only once.
- Update FFmpeg to the latest secure version.
- Test thoroughly after applying the fix.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2025-12343.
| URL | Resource |
|---|---|
| https://access.redhat.com/security/cve/CVE-2025-12343 | |
| https://bugzilla.redhat.com/show_bug.cgi?id=2406533 |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2025-12343 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2025-12343
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2025-12343 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2025-12343 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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New CVE Received by [email protected]
Feb. 18, 2026
Action Type Old Value New Value Added Description A flaw was found in FFmpeg’s TensorFlow backend within the libavfilter/dnn_backend_tf.c source file. The issue occurs in the dnn_execute_model_tf() function, where a task object is freed multiple times in certain error-handling paths. This redundant memory deallocation can lead to a double-free condition, potentially causing FFmpeg or any application using it to crash when processing TensorFlow-based DNN models. This results in a denial-of-service scenario but does not allow arbitrary code execution under normal conditions. Added CVSS V3.1 AV:L/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:L Added CWE CWE-415 Added Reference https://access.redhat.com/security/cve/CVE-2025-12343 Added Reference https://bugzilla.redhat.com/show_bug.cgi?id=2406533