CVE-2025-55559
Description
A flaw was found in TensorFlow. When a model uses tf.keras.layers.Conv2D with padding='valid' and is compiled using XLA, the compiler miscalculates the output shape and ends up with a negative dimension. This causes the process to crash during compilation, leading to a denial of service. The same operation works correctly in eager mode because it checks dimensions dynamically, but under XLA the static shape calculation fails and stops execution.
Statement
The impact is MODERATE because the flaw only causes a denial of service and cannot be used to access data or execute arbitrary code. It happens during local model compilation when TensorFlow’s XLA tries to compile a Conv2D layer with incompatible input and kernel sizes. The error forces the process to abort, interrupting model training or inference. This requires the ability to run or modify TensorFlow model code.
Common Vulnerability Scoring System (CVSS) Score Details
Info alert:Important note
CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).
The following CVSS metrics and score provided are preliminary and subject to review.
CVSS v3 Score Breakdown
| Red Hat | NVD | cve.org | |
|---|---|---|---|
| Base Score | 6.5 | N/A | 7.5 |
| Attack Vector | Network | N/A | Network |
| Attack Complexity | Low | N/A | Low |
| Privileges Required | Low | N/A | None |
| User Interaction | None | N/A | None |
| Scope | Unchanged | N/A | Unchanged |
| Confidentiality | None | N/A | None |
| Integrity Impact | None | N/A | None |
| Availability Impact | High | N/A | High |
Vector
Red Hat: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
cve.org: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
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