CVE-2025-55556: 
TensorFlow vulnerability analysis and mitigation

TensorFlow v2.18.0 was discovered to output random results when compiling Embedding, leading to unexpected behavior in the application (NVD, GitHub Advisory). The vulnerability was disclosed on September 25, 2025, and affects TensorFlow installations running version 2.18.0 or earlier.

The vulnerability specifically affects the TensorFlow API tf.keras.layers.Embedding when compiled with the XLA compiler. The issue manifests when the model compilation process results in unexpected and random output values, differing from the expected behavior of the Embedding layer. The vulnerability has been assigned a CVSS v3.1 base score of 6.5 (Medium) with the vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:L/A:L (Red Hat).

When exploited, this vulnerability can result in silent incorrectness, causing the TensorFlow model to make wrong or dangerous decisions. This is particularly concerning as the random outputs could lead to unexpected behavior in applications relying on the Embedding layer functionality (GitHub Advisory).

According to Red Hat's security advisory, mitigation for this issue is either not available or the currently available options do not meet their Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability (Red Hat).