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

CVE-2021-37690

Disclosure Date: August 13, 2021
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Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as MutableHashTableShape) produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. ShapeRefiner is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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CVSS V3 Severity and Metrics
Base Score:
6.6 Medium
Impact Score:
4.7
Exploitability Score:
1.8
Vector:
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
Attack Vector (AV):
Local
Attack Complexity (AC):
Low
Privileges Required (PR):
Low
User Interaction (UI):
None
Scope (S):
Unchanged
Confidentiality (C):
Low
Integrity (I):
Low
Availability (A):
High

General Information

Vendors

  • google

Products

  • tensorflow,
  • tensorflow 2.5.0,
  • tensorflow 2.6.0

Additional Info

Technical Analysis