CVE-2020-15213

Published Sep 25, 2020

Last updated 3 years ago

Overview

Description
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
Source
security-advisories@github.com
NVD status
Analyzed

Risk scores

CVSS 3.1

Type
Primary
Base score
4
Impact score
1.4
Exploitability score
2.2
Vector string
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L
Severity
MEDIUM

CVSS 2.0

Type
Primary
Base score
4.3
Impact score
2.9
Exploitability score
8.6
Vector string
AV:N/AC:M/Au:N/C:N/I:N/A:P

Weaknesses

nvd@nist.gov
CWE-770
security-advisories@github.com
CWE-119

Social media

Hype score
Not currently trending

Configurations