Attacker Value
Unknown
(0 users assessed)
Exploitability
Unknown
(0 users assessed)
User Interaction
None
Privileges Required
None
Attack Vector
Network
0

CVE-2020-15206

Disclosure Date: September 25, 2020
Add MITRE ATT&CK tactics and techniques that apply to this CVE.

Description

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.

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CVSS V3 Severity and Metrics
Base Score:
7.5 High
Impact Score:
3.6
Exploitability Score:
3.9
Vector:
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
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

General Information

Weaknesses

Technical Analysis