Heap out of bounds read in `MaxPoolGradWithArgmax`
Impact
The implementation of tf.raw_ops.MaxPoolGradWithArgmax can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:
import tensorflow as tf
input = tf.constant([10.0, 10.0, 10.0], shape=[1, 1, 3, 1], dtype=tf.float32)
grad = tf.constant([10.0, 10.0, 10.0, 10.0], shape=[1, 1, 1, 4], dtype=tf.float32)
argmax = tf.constant([1], shape=[1], dtype=tf.int64)
ksize = [1, 1, 1, 1]
strides = [1, 1, 1, 1]
tf.raw_ops.MaxPoolGradWithArgmax(
input=input, grad=grad, argmax=argmax, ksize=ksize, strides=strides,
padding='SAME', include_batch_in_index=False)The implementation uses the same value to index in two different arrays but there is no guarantee that the sizes are identical.
Patches
We have patched the issue in GitHub commit dcd7867de0fea4b72a2b34bd41eb74548dc23886.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 by Ying Wang and Yakun Zhang of Baidu X-Team.
Software afectado
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| Plataforma | Paquete | Versiones vulnerables | Corregida en |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-cpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
| Python (PyPI) | tensorflow-gpu | < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 |
Referencias
- https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-545v-42p7-98fq
- https://nvd.nist.gov/vuln/detail/CVE-2021-29570
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-498.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-696.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-207.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L- Debilidad (CWE)
CWE-125- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 14.05.2021
- Actualizado
- 11.10.2026 13:19
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2021-207 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-498 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-696 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-545v-42p7-98fq - CC BY 4.0
Historial de vulnerabilidades: tensorflow-cpu
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
- 430
- Primera → última
- 04.2019 07.2024
- Sin corrección
- 0
- Explotada en ataques
- 0
Distribución por gravedad
- Crítica 6
- Alta 111
- Media 208
- Baja 105
Divulgaciones por año
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
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Heap out of bounds read in `MaxPoolGradWithArgmax` esta entrada
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