Vulnerability Monitor

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CVE-2020-15206

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.

Published

2020-09-25T19:15:15.917

Last Modified

2024-11-21T05:05:05.090

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 9.0 (CRITICAL)

CVSSv2 Vector

AV:N/AC:L/Au:N/C:N/I:N/A:P

  • Access Vector: NETWORK
  • Access Complexity: LOW
  • Authentication: NONE
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: PARTIAL
Exploitability Score

10.0

Impact Score

2.9

Weaknesses
  • Type: Secondary
    CWE-20
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 1.15.4 Yes
Application google tensorflow < 2.0.3 Yes
Application google tensorflow < 2.1.2 Yes
Application google tensorflow < 2.2.1 Yes
Application google tensorflow < 2.3.1 Yes
Operating System opensuse leap 15.2 Yes
References