CVE-2020-15212

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 writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. 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 the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. 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
8.6
Impact score
4.7
Exploitability score
3.9
Vector string
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
Severity
HIGH

CVSS 2.0

Type
Primary
Base score
7.5
Impact score
6.4
Exploitability score
10
Vector string
AV:N/AC:L/Au:N/C:P/I:P/A:P

Weaknesses

nvd@nist.gov
CWE-787
security-advisories@github.com
CWE-787

Social media

Hype score
Not currently trending

Configurations