Description
In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
Published: 2020-12-10
Score: 4.4 Medium
EPSS: < 1% Very Low
KEV: No
Impact: n/a
Action: n/a
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Advisories
Source ID Title
EUVD EUVD EUVD-2020-0213 In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
Github GHSA Github GHSA GHSA-qhxx-j73r-qpm2 Uninitialized memory access in TensorFlow
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Google Tensorflow
cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2024-08-04T15:56:04.617Z

Reserved: 2020-10-01T00:00:00.000Z

Link: CVE-2020-26266

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Modified

Published: 2020-12-10T23:15:12.647

Modified: 2024-11-21T05:19:42.273

Link: CVE-2020-26266

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

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Weaknesses