CVE-2020-15197

MEDIUM
Published September 25, 2020

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...

Full analysis pending. Showing NVD description excerpt.

Affected Systems

Package Ecosystem Vulnerable Range Patched
tensorflow pip No patch

Do you use tensorflow? You're affected.

Severity & Risk

CVSS 3.1
6.3 / 10
EPSS
N/A
KEV Status
Not in KEV
Sophistication
N/A

Recommended Action

No patch available

Monitor for updates. Consider compensating controls or temporary mitigations.

Compliance Impact

Compliance analysis pending. Sign in for full compliance mapping when available.

Technical Details

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.

Weaknesses (CWE)

CVSS Vector

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H

Timeline

Published
September 25, 2020
Last Modified
November 21, 2024
First Seen
September 25, 2020