CVE-2020-15214: In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids ar...

Description

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based 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 sorted, 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.

Metrics

CVSS 3.1

8.1/10

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H

EPSS Probability

0.56%

42.1th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

CWE-787

Affected Software

Vendor	Product	Versions
Google	Tensorflow	>= 2.2.0, < 2.2.1
Google	Tensorflow	>= 2.3.0, < 2.3.1

References

https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178aPatch, Third Party Advisory
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvmExploit, Third Party Advisory
https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178aPatch, Third Party Advisory
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p2cq-cprg-frvmExploit, Third Party Advisory

Timeline

Published: Sep 25, 2020
Last Modified: Jun 17, 2026
Status: Modified

Frequently Asked Questions

What is CVE-2020-15214?

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based 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 sorted, 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.

How severe is CVE-2020-15214?

CVE-2020-15214 has a CVSS score of 8.1/10 (HIGH severity). The EPSS model estimates a 0.56% probability of exploitation in the next 30 days.

How do I fix CVE-2020-15214?

Check the vendor references and advisories linked above for patched versions and mitigation guidance. You can also run a Strix scan to test if your systems are affected.