CVE-2020-15213

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.
Configurations

Configuration 1 (hide)

OR cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*
cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*

History

18 Nov 2021, 17:28

Type Values Removed Values Added
CWE CWE-119

17 Aug 2021, 13:21

Type Values Removed Values Added
CPE cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:lite:*:*:* cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*

Information

Published : 2020-09-25 19:15

Updated : 2023-12-10 13:41


NVD link : CVE-2020-15213

Mitre link : CVE-2020-15213

CVE.ORG link : CVE-2020-15213


JSON object : View

Products Affected

google

  • tensorflow
CWE
CWE-770

Allocation of Resources Without Limits or Throttling

CWE-119

Improper Restriction of Operations within the Bounds of a Memory Buffer