title: `CHECK`-failures in binary ops in Tensorflow
description: Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don't match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
problem types: CWE-617: Reachable Assertion
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: >= 2.7.0, < 2.7.1
status: affected, version: >= 2.6.0, < 2.6.3
status: affected, version: < 2.5.3
}
metrics:
cvssV3_1: [
attackComplexity: LOW
attackVector: NETWORK
availabilityImpact: HIGH
baseScore: 6.5
baseSeverity: MEDIUM
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
version: 3.1
]