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CVE-2022-23594

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Date: February 4, 2022

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.

Language: C++

Severity Score

Severity Score

Weakness Type (CWE)

Out-of-bounds Write

CWE-787

Out-of-bounds Read

CWE-125

Top Fix

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Upgrade to version tensorflow - 2.7.1,2.8.0;tensorflow-cpu - 2.7.1,2.8.0;tensorflow-gpu - 2.7.1,2.8.0

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CVSS v3.1

Base Score:
Attack Vector (AV): LOCAL
Attack Complexity (AC): LOW
Privileges Required (PR): LOW
User Interaction (UI): NONE
Scope (S): UNCHANGED
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): HIGH

CVSS v2

Base Score:
Access Vector (AV): LOCAL
Access Complexity (AC): LOW
Authentication (AU): NONE
Confidentiality (C): NONE
Integrity (I): NONE
Availability (A): PARTIAL
Additional information:

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