title: Out of bounds read in Tensorflow
description: Tensorflow is an Open Source Machine Learning Framework. The TFG dialect of TensorFlow (MLIR) makes several assumptions about the incoming `GraphDef` before converting it to the MLIR-based dialect. If an attacker changes the `SavedModel` format on disk to invalidate these assumptions and the `GraphDef` is then converted to MLIR-based IR then they can cause a crash in the Python interpreter. Under certain scenarios, heap OOB read/writes are possible. These issues have been discovered via fuzzing and it is possible that more weaknesses exist. We will patch them as they are discovered.
problem types: CWE-125: Out-of-bounds Read
affected:
{
product: tensorflow
vendor: tensorflow
versions:
status: affected, version: >= 2.7.0, < 2.8.0
}
metrics:
cvssV3_1: [
attackComplexity: LOW
attackVector: LOCAL
availabilityImpact: HIGH
baseScore: 8.8
baseSeverity: HIGH
confidentialityImpact: HIGH
integrityImpact: HIGH
privilegesRequired: LOW
scope: CHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
version: 3.1
]