CVE Vulnerability

CVE-2022-23594

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.

2.1 /10

CVSS v2.0 :

V3 Legend

Vector :

Exploitability : 3.9 / Impact : 2.9

Attack Vector

Attack Complexity

Privileges Required

User Interaction

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact PARTIAL

Scope

5.5 /10

CVSS v3.0 : MEDIUM

V3 Legend

Vector :

Exploitability : 1.8 / Impact : 3.6

Attack Vector LOCAL

Attack Complexity LOW

Privileges Required LOW

User Interaction NONE

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact HIGH

Scope UNCHANGED

References
Link Resource
https://github.com/tensorflow/tensorflow/tree/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/ir/importexport Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9x52-887g-fhc2 Third Party Advisory
Configurations

Configuration 1

cpe:2.3:a:google:tensorflow:2.7.0:*:*:*:*:*:*:*
Information

Published : 2022-02-04 11:15

Updated : 2022-02-10 06:15

NVD link : CVE-2022-23594

Mitre link : CVE-2022-23594

Products Affected
No products.
CWE
CWE-125

Out-of-bounds Read

CWE-787