CVE Vulnerability

CVE-2020-15197

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.

3.5 /10

CVSS v2.0 :

V3 Legend

Vector :

Exploitability : 6.8 / Impact : 2.9

Attack Vector

Attack Complexity

Privileges Required

User Interaction

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact PARTIAL

Scope

6.3 /10

CVSS v3.0 : MEDIUM

V3 Legend

Vector :

Exploitability : 1.8 / Impact : 4

Attack Vector NETWORK

Attack Complexity HIGH

Privileges Required LOW

User Interaction NONE

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact HIGH

Scope CHANGED

References
Link Resource
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qc53-44cj-vfvx Exploit Third Party Advisory
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1 Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02 Patch Third Party Advisory
Configurations

Configuration 1

cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:*
Information

Published : 2020-09-25 07:15

Updated : 2021-08-17 01:21

NVD link : CVE-2020-15197

Mitre link : CVE-2020-15197

Products Affected
No products.
CWE
CWE-20

CWE-617