CVE-2021-29547: Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`

Severity: medium (CVSS 5.5 v3.1)
Exploited in the wild: not listed in CISA KEV
EPSS: 0.2% probability of exploitation in the next 30 days
Public exploit or detection template: yes
Published: 2021-05-14 · updated 2026-06-17
Weakness: CWE-125

Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected products

tensorflow: before 2.1.4; from 2.2.0 before 2.2.3; from 2.3.0 before 2.3.3; from 2.4.0 before 2.4.2 — fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2

How to fix

Upgrade to a fixed version: tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2. Check the vendor advisory for mitigations.

References

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