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CVE-2021-37651

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Date: August 12, 2021

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.FractionalAvgPoolGrad` can be tricked into accessing data outside of bounds of heap allocated buffers. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/fractional_avg_pool_op.cc#L205) does not validate that the input tensor is non-empty. Thus, code constructs an empty `EigenDoubleMatrixMap` and then accesses this buffer with indices that are outside of the empty area. We have patched the issue in GitHub commit 0f931751fb20f565c4e94aa6df58d54a003cdb30. 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.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Out-of-bounds Write

CWE-787

Top Fix

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Upgrade Version

Upgrade to version tensorflow - 2.3.4, 2.4.3, 2.5.1, 2.6.0, tensorflow-cpu - 2.3.4, 2.4.3, 2.5.1, 2.6.0, tensorflow-gpu - 2.3.4, 2.4.3, 2.5.1, 2.6.0

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CVSS v3.1

Base Score:
Attack Vector (AV): LOCAL
Attack Complexity (AC): LOW
Privileges Required (PR): LOW
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): HIGH
Integrity (I): HIGH
Availability (A): HIGH

CVSS v2

Base Score:
Access Vector (AV): LOCAL
Access Complexity (AC): LOW
Authentication (AU): NONE
Confidentiality (C): PARTIAL
Integrity (I): PARTIAL
Availability (A): PARTIAL
Additional information:

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