CVE-2022-29196Medium· 5.5▾ SunlitMissing validation causes denial of service via `Conv3DBackpropFilterV2`
▾ Sunlit zone — Low / medium · no exploitation signal
impact 30.3 · likelihood 0.1 · exploitation 0
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Exploit-prediction probability, daily snapshots since Jul 8.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
Last analysed / modified upstream
0.3%
0.3% → 0.3%
The implementation of tf.raw_ops.Conv3DBackpropFilterV2 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.raw_ops.Conv3DBackpropFilterV2(
input=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16),
filter_sizes=tf.constant(0, shape=[], dtype=tf.int32),
out_backprop=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16),
strides=[1, 1, 1, 1, 1],
padding="VALID",
data_format="NDHWC",
dilations=[1, 1, 1, 1, 1])
The code does not validate that the filter_sizes argument is a vector.
We have patched the issue in GitHub commit 174c5096f303d5be7ed2ca2662b08371bff4ab88.
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.
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This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.
tensorflow < 2.6.4tensorflow >= 2.7.0, < 2.7.2tensorflow >= 2.8.0, < 2.8.1tensorflow-cpu < 2.6.4tensorflow-cpu >= 2.7.0, < 2.7.2tensorflow-cpu >= 2.8.0, < 2.8.1tensorflow-gpu < 2.6.4tensorflow-gpu >= 2.7.0, < 2.7.2tensorflow-gpu >= 2.8.0, < 2.8.1Upgrade to a patched release:
tensorflow 2.6.4tensorflow 2.7.2tensorflow 2.8.1tensorflow-cpu 2.6.4tensorflow-cpu 2.7.2tensorflow-cpu 2.8.1tensorflow-gpu 2.6.4tensorflow-gpu 2.7.2tensorflow-gpu 2.8.1Connected by shared product, vendor, weakness, or advisory.
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