Missing validation causes denial of service via `Conv3DBackpropFilterV2`
Impact
The implementation of tf.raw_ops.UnsortedSegmentJoin does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:
import tensorflow as tf
tf.strings.unsorted_segment_join(
inputs=['123'],
segment_ids=[0],
num_segments=-1)The code assumes num_segments is a positive scalar but there is no validation:
const Tensor& num_segments_tensor = context->input(2);
auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()();
// ...
Tensor* output_tensor = nullptr;
TensorShape output_shape =
GetOutputShape(input_shape, segment_id_shape, num_segments);Since this value is used to allocate the output tensor, a negative value would result in a CHECK-failure (assertion failure), as per TFSA-2021-198.
Patches
We have patched the issue in GitHub commit 84563f265f28b3c36a15335c8b005d405260e943 and GitHub commit 20cb18724b0bf6c09071a3f53434c4eec53cc147.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported externally via a GitHub issue.
Software afectado
Haz clic en una tecnología para ver todas sus vulnerabilidades.
| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
| Python (PyPI) | tensorflow-cpu | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
| Python (PyPI) | tensorflow-gpu | < 2.6.4, >= 2.7.0, < 2.7.2, >= 2.8.0, < 2.8.1 | 2.6.4, 2.7.2, 2.8.1 |
Referencias
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx9q-2mx4-m4pg
- https://nvd.nist.gov/vuln/detail/CVE-2022-29204
- https://github.com/tensorflow/tensorflow/commit/20cb18724b0bf6c09071a3f53434c4eec53cc147
- https://github.com/tensorflow/tensorflow/commit/84563f265f28b3c36a15335c8b005d405260e943
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L83-L14
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md
- https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
- https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
- https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
- https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0
- https://pypi.org/project/tensorflow-gpu
- https://github.com/advisories/GHSA-hx9q-2mx4-m4pg
- https://pypi.org/project/tensorflow
- https://pypi.org/project/tensorflow-cpu
- Vector CVSS
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Debilidad (CWE)
CWE-191, CWE-20- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 24.05.2022
- Actualizado
- 11.10.2026 14:18
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2026-1010 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3203 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-hx9q-2mx4-m4pg - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3342 - PyPA Advisory Database; CC BY 4.0
Historial de vulnerabilidades: tensorflow
Todas las vulnerabilidades publicadas de este paquete (Python (PyPI)), de la más reciente a la más antigua. Muestra si es un fallo aislado o un paquete que hay que vigilar.
- Entradas en total
- 433
- Primera → última
- 04.2019 07.2024
- Sin corrección
- 0
- Explotada en ataques
- 0
Distribución por gravedad
- Crítica 6
- Alta 112
- Media 210
- Baja 105
Divulgaciones por año
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Missing validation causes denial of service via `Conv3DBackpropFilterV2` esta entrada
Identifica las vulnerabilidades de tu aplicación
Con la integración de DockRay y el inventario de software activado, DockRay compara las versiones notificadas de los componentes con las vulnerabilidades conocidas y avisa de las coincidencias confirmadas. La cobertura depende de la tecnología compatible y de los avisos disponibles.