Vulnerability Monitor

The vendors, products, and vulnerabilities you care about

CVE-2021-37690

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.

Published

2021-08-13T00:15:07.170

Last Modified

2024-11-21T06:15:42.697

Status

Modified

Source

[email protected]

Severity

CVSSv3.1: 6.6 (MEDIUM)

CVSSv2 Vector

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

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

3.9

Impact Score

6.4

Weaknesses
  • Type: Primary
    CWE-416
Affected Vendors & Products
Type Vendor Product Version/Range Vulnerable?
Application google tensorflow < 2.3.4 Yes
Application google tensorflow < 2.4.3 Yes
Application google tensorflow 2.5.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
Application google tensorflow 2.6.0 Yes
References