PT-2020-14281 · Google+1 · Tensorflow+1

Published

2020-09-25

·

Updated

2024-03-06

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CVE-2020-15210

CVSS v4.0

8.3

High

VectorAV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N
Name of the Vulnerable Software and Affected Versions TensorFlow versions prior to 1.15.4 TensorFlow versions prior to 2.0.3 TensorFlow versions prior to 2.1.2 TensorFlow versions prior to 2.2.1 TensorFlow versions prior to 2.3.1
Description If a TFLite saved model uses the same tensor as both input and output of an operator, it can cause a segmentation fault or memory corruption, depending on the operator.
Recommendations For versions prior to 1.15.4, upgrade to TensorFlow 1.15.4. For versions prior to 2.0.3, upgrade to TensorFlow 2.0.3. For versions prior to 2.1.2, upgrade to TensorFlow 2.1.2. For versions prior to 2.2.1, upgrade to TensorFlow 2.2.1. For versions prior to 2.3.1, upgrade to TensorFlow 2.3.1. As a temporary workaround, consider adding a custom Verifier to the model loading code to ensure that no operator reuses tensors as both inputs and outputs.

Exploit

Fix

Memory Corruption

RCE

Weakness Enumeration

Related Identifiers

BIT-TENSORFLOW-2020-15210
CVE-2020-15210
GHSA-X9J7-X98R-R4W2
OPENSUSE-SU-2020:1766-1
OPENSUSE-SU-2020_1766-1
PYSEC-2020-133
PYSEC-2020-290
PYSEC-2020-325

Affected Products

Suse
Tensorflow