CVE-2021-37658High· 7.1▾ TwilightReference binding to nullptr in `MatrixSetDiagV*` ops
▾ Twilight zone — High severity, or a signal on a lesser flaw
impact 39.1 · likelihood 0 · 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
0.2%
An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixSetDiagV*:
import tensorflow as tf
tf.raw_ops.MatrixSetDiagV3(
input=[1,2,3],
diagonal=[1,1],
k=[],
align='RIGHT_LEFT')
The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:
auto& diag_index = context->input(1);
...
lower_diag_index = diag_index.flat<int32>()(0);
We have patched the issue in GitHub commit ff8894044dfae5568ecbf2ed514c1a37dc394f1b.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
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This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
tensorflow < 2.3.4tensorflow >= 2.4.0, < 2.4.3tensorflow >= 2.5.0, < 2.5.1tensorflow-cpu < 2.3.4tensorflow-cpu >= 2.4.0, < 2.4.3tensorflow-cpu >= 2.5.0, < 2.5.1tensorflow-gpu < 2.3.4tensorflow-gpu >= 2.4.0, < 2.4.3tensorflow-gpu >= 2.5.0, < 2.5.1Upgrade to a patched release:
tensorflow 2.3.4tensorflow 2.4.3tensorflow 2.5.1tensorflow-cpu 2.3.4tensorflow-cpu 2.4.3tensorflow-cpu 2.5.1tensorflow-gpu 2.3.4tensorflow-gpu 2.4.3tensorflow-gpu 2.5.1Connected by shared product, vendor, weakness, or advisory.
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