CVE-2020-15206: Denial of Service in Tensorflow

Severity: high (CVSS 7.5 v3.1)
Exploited in the wild: not listed in CISA KEV
EPSS: 1.0% probability of exploitation in the next 30 days
Public exploit or detection template: yes
Published: 2020-09-25 · updated 2026-06-17
Weakness: CWE-20

Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Affected products

tensorflow: before 1.15.4; from 2.0.0 before 2.0.3; from 2.1.0 before 2.1.2; from 2.2.0 before 2.2.1; from 2.3.0 before 2.3.1 — fixed in 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
openSUSE Leap: 15.2

How to fix

Upgrade to a fixed version: tensorflow 1.15.4, 2.0.3, 2.1.2, 2.2.1. Check the vendor advisory for mitigations.

References

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