title: Heap buffer overflow in `Conv2DBackpropFilter`
description: TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a heap buffer overflow to occur in `Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/1b0296c3b8dd9bd948f924aa8cd62f87dbb7c3da/tensorflow/core/kernels/conv_grad_filter_ops.cc#L495-L497) computes the size of the filter tensor but does not validate that it matches the number of elements in `filter_sizes`. Later, when reading/writing to this buffer, code uses the value computed here, instead of the number of elements in the tensor. 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-120: Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')
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
]