Input validation error in TensorFlow and nginx - CVE-2020-15197

 

Input validation error in TensorFlow and nginx - CVE-2020-15197

Published: September 25, 2020 / Updated: June 28, 2025


Vulnerability identifier: #VU47295
CSH Severity: Medium
CVSSv4.0: CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/E:U/U:Green
CVE-ID: CVE-2020-15197
CWE-ID: CWE-20
Exploitation vector: Remote access
Exploit availability: No public exploit available
Vulnerable software:
TensorFlow
nginx
Software vendor:
TensorFlow
F5 Networks

Description

The vulnerability allows a remote authenticated user to a crash the entire system.

In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.


Remediation

Install update from vendor's website.

External links