CVE-2020-15212: 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 inserti...

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.

Metrics

CVSS 3.1

8.6/10

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

EPSS Probability

0.61%

44.6th percentile

Probability of exploitation in the next 30 days. Learn more

Weakness Enumeration

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-hx2x-85gr-wrpqExploit, Patch, 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-hx2x-85gr-wrpqExploit, Patch, Third Party Advisory

Timeline

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

Frequently Asked Questions

What is CVE-2020-15212?

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.

How severe is CVE-2020-15212?

CVE-2020-15212 has a CVSS score of 8.6/10 (HIGH severity). The EPSS model estimates a 0.61% probability of exploitation in the next 30 days.

How do I fix CVE-2020-15212?

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.