Description
In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Published: 2020-09-25
Score: 6.5 Medium
EPSS: < 1% Very Low
KEV: No
Impact: n/a
Action: n/a
AI Analysis

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Remediation

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Tracking

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Advisories
Source ID Title
EUVD EUVD EUVD-2020-0206 In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Github GHSA Github GHSA GHSA-x9j7-x98r-r4w2 Segmentation fault in tensorflow-lite
History

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cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published:

Updated: 2024-08-04T13:08:22.871Z

Reserved: 2020-06-25T00:00:00.000Z

Link: CVE-2020-15210

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Modified

Published: 2020-09-25T19:15:16.307

Modified: 2024-11-21T05:05:05.720

Link: CVE-2020-15210

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

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Weaknesses