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PYSEC-2021-468

Published May 14, 2021·Last modified Dec 6, 2023
Affected Components(0)

No affected components available

Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in Conv2DBackpropFilter. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in filter_sizes. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Risk Scores
Base Score
0.0

Measures severity based on intrinsic characteristics of the vulnerability, independent of environment.

Threat Intelligence
0.0

No exploitation activity has been observed at this time. Continue routine monitoring.

EPSS
0.21%

The exploit probability is very low. The vulnerability is unlikely to be exploited in the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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