title: Heap buffer overflow in Tensorflow
description: In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
problem types: {"CWE-20":"Improper Input Validation"}
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: = 2.3.0
}
metrics:
cvssV3_1: [
attackComplexity: HIGH
attackVector: NETWORK
availabilityImpact: NONE
baseScore: 4.8
baseSeverity: MEDIUM
confidentialityImpact: LOW
integrityImpact: LOW
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
version: 3.1
]