title: Heap buffer overflow in Tensorflow
description: In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
problem types: {"CWE-122":"Heap-based Buffer Overflow"}
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: >= 2.3.0, < 2.3.1
}
metrics:
cvssV3_1: [
attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 5.4
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: NONE
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N
version: 3.1
]