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MEDIUM · 6.5

CVE-2020-15210

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 ...

Vulnerability 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.

CVSS Score

6.5

MEDIUM

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H
Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
NONE
Integrity
LOW
Availability
HIGH

Affected Products

VendorProductVersions
GoogleTensorflow< 1.15.4
OpensuseLeap15.2

Related Weaknesses (CWE)

CWE-20CWE-787

References

FAQ

What is CVE-2020-15210?

CVE-2020-15210 is a vulnerability with a CVSS score of 6.5 (MEDIUM). 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 ...

How severe is CVE-2020-15210?

CVE-2020-15210 has been rated MEDIUM with a CVSS base score of 6.5/10. Review the CVSS metrics above for detailed severity breakdown.

Is there a patch for CVE-2020-15210?

Check the references section above for vendor advisories and patch information. Affected products include: Google Tensorflow, Opensuse Leap.