Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
Low
Attack Vector
Network
0

CVE-2020-15197

Disclosure Date: September 25, 2020
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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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CVSS V3 Severity and Metrics
Base Score:
6.3 Medium
Impact Score:
4
Exploitability Score:
1.8
Vector:
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
Attack Vector (AV):
Network
Attack Complexity (AC):
High
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Changed
Confidentiality (C):
None
Integrity (I):
None
Availability (A):
High

General Information

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Additional Info

Technical Analysis