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Case File

CVE-2020-15197

MEDIUM · CVSS 6.3 EPSS 0.73% Public Exploit

Source: NVD + CISA KEV + EPSS (historical backfill) · Published 2020-09-25 · Last synced 2026-08-04

CyberRota Analysis

This is a medium severity vulnerability with a CVSS score of 6.3. Public exploit code or proof-of-concept references have been detected in its references. It may lead to a denial-of-service condition.

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-2020-15197
Severity
MEDIUM
CVSS
6.3
EPSS
0.73%

Original NVD Description

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.

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