CVE-2020-15208: Data corruption in tensorflow-lite

Severity: critical (CVSS 9.8 v3.1)
Exploited in the wild: not listed in CISA KEV
EPSS: 0.9% probability of exploitation in the next 30 days
Public exploit or detection template: yes
Published: 2020-09-25 · updated 2026-06-17
Weakness: CWE-125

Description

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, 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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