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Case File

CVE-2021-37657

HIGH · CVSS 7.1 EPSS 0.17% Public Exploit

Source: NVD + CISA KEV + EPSS (historical backfill) · Published 2021-08-12 · Last synced 2026-08-04

CyberRota Analysis

This is a high severity vulnerability with a CVSS score of 7.1. It affects GitHub. Public exploit code or proof-of-concept references have been detected in its references.

Public Exploit Signal

A public exploit, PoC, GitHub repository or Metasploit reference was detected for this CVE.

Note: these links are listed for security research and verification purposes only.

CVE
CVE-2021-37657
Severity
HIGH
CVSS
7.1
EPSS
0.17%
GitHub

Original NVD Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) 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. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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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