title: Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`
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.
problem types: CWE-125: Out-of-bounds Read
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: < 2.1.4
status: affected, version: >= 2.2.0, < 2.2.3
status: affected, version: >= 2.3.0, < 2.3.3
status: affected, version: >= 2.4.0, < 2.4.2
}
metrics:
cvssV3_1: [
attackComplexity: HIGH
attackVector: LOCAL
availabilityImpact: LOW
baseScore: 2.5
baseSeverity: LOW
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
version: 3.1
]