title: Stack overflow in Tensorflow
description: Tensorflow is an Open Source Machine Learning Framework. The `GraphDef` format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a `GraphDef` containing a fragment such as the following can be consumed when loading a `SavedModel`. This would result in a stack overflow during execution as resolving each `NodeDef` means resolving the function itself and its nodes. 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-400: Uncontrolled Resource Consumption
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: 7.5
baseSeverity: HIGH
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: NONE
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
version: 3.1
]