Описание
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.
| Релиз | Статус | Примечание |
|---|---|---|
| devel | needs-triage | |
| esm-apps/bionic | needs-triage | |
| esm-apps/focal | needs-triage | |
| esm-apps/jammy | needs-triage | |
| esm-apps/noble | needs-triage | |
| esm-apps/xenial | needs-triage | |
| jammy | needs-triage | |
| noble | needs-triage | |
| plucky | ignored | end of life, was needs-triage |
| questing | needs-triage |
Показывать по
| Релиз | Статус | Примечание |
|---|---|---|
| devel | DNE | |
| esm-infra-legacy/trusty | needs-triage | |
| jammy | DNE | |
| noble | DNE | |
| plucky | DNE | |
| questing | DNE | |
| upstream | needs-triage |
Показывать по
Ссылки на источники
EPSS
3.3 Low
CVSS3
Связанные уязвимости
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.
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.
A flaw was found in FFmpeg\u2019s TensorFlow backend within the libavf ...
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.
EPSS
3.3 Low
CVSS3