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nvd[email protected]NVD:CVE-2020-15265
HistoryOct 21, 2020 - 9:15 p.m.

CVE-2020-15265

2020-10-2121:15:12
CWE-125
web.nvd.nist.gov
7
tensorflow security vulnerability
out of bounds access
cve-2020-15265
invalid axis.

CVSS2

5

Attack Vector

NETWORK

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

PARTIAL

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

CVSS3

7.5

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS

0.002

Percentile

56.9%

In Tensorflow before version 2.4.0, an attacker can pass an invalid axis value to tf.quantization.quantize_and_dequantize. This results in accessing a dimension outside the rank of the input tensor in the C++ kernel implementation. However, dim_size only does a DCHECK to validate the argument and then uses it to access the corresponding element of an array. Since in normal builds, DCHECK-like macros are no-ops, this results in segfault and access out of bounds of the array. The issue is patched in eccb7ec454e6617738554a255d77f08e60ee0808 and TensorFlow 2.4.0 will be released containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Affected configurations

Nvd
Node
googletensorflowRange<2.4.0-
VendorProductVersionCPE
googletensorflow*cpe:2.3:a:google:tensorflow:*:*:*:*:-:*:*:*

CVSS2

5

Attack Vector

NETWORK

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

PARTIAL

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

CVSS3

7.5

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

NONE

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

NONE

Availability Impact

HIGH

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS

0.002

Percentile

56.9%

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