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CVE-2020-15206

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Date: September 25, 2020

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. Fixed were added in commits f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Language: Python

Severity Score

Severity Score

Weakness Type (CWE)

Input Validation

CWE-20

Top Fix

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Upgrade Version

Upgrade to version 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1

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CVSS v3.1

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

CVSS v2

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

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