CVE-2022-21739Medium· 6.5▾ SunlitNull pointer dereference in TensorFlow
▾ Sunlit zone — Low / medium · no exploitation signal
impact 35.8 · likelihood 0.2 · exploitation 0
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Exploit-prediction probability, daily snapshots since Jul 13.
Disclosure to exploitation, from the record and what we observed since indexing it.
Disclosed via OSV
0.8%
0.8% → 0.8%
Last analysed / modified upstream
The implementation of QuantizedMaxPool has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer.
import tensorflow as tf
tf.raw_ops.QuantizedMaxPool(
input = tf.constant([[[[4]]]], dtype=tf.quint8),
min_input = [],
max_input = [1],
ksize = [1, 1, 1, 1],
strides = [1, 1, 1, 1],
padding = "SAME", name=None
)
We have patched the issue in GitHub commit 53b0dd6dc5957652f35964af16b892ec9af4a559.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
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This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.
tensorflow < 2.5.3tensorflow >= 2.6.0, < 2.6.3tensorflow >= 2.7.0, < 2.7.1tensorflow-cpu < 2.5.3tensorflow-cpu >= 2.6.0, < 2.6.3tensorflow-cpu >= 2.7.0, < 2.7.1tensorflow-gpu < 2.5.3tensorflow-gpu >= 2.6.0, < 2.6.3tensorflow-gpu >= 2.7.0, < 2.7.1Upgrade to a patched release:
tensorflow 2.5.3tensorflow 2.6.3tensorflow 2.7.1tensorflow-cpu 2.5.3tensorflow-cpu 2.6.3tensorflow-cpu 2.7.1tensorflow-gpu 2.5.3tensorflow-gpu 2.6.3tensorflow-gpu 2.7.1Connected by shared product, vendor, weakness, or advisory.
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