CVE Vulnerability

CVE-2020-15265

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.

5 /10

CVSS v2.0 :

V3 Legend

Vector :

Exploitability : 10 / Impact : 2.9

Attack Vector

Attack Complexity

Privileges Required

User Interaction

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact PARTIAL

Scope

7.5 /10

CVSS v3.0 : HIGH

V3 Legend

Vector :

Exploitability : 3.9 / Impact : 3.6

Attack Vector NETWORK

Attack Complexity LOW

Privileges Required NONE

User Interaction NONE

Confidentiality Impact NONE

Integrity Impact NONE

Availability Impact HIGH

Scope UNCHANGED

References
Link Resource
https://github.com/tensorflow/tensorflow/commit/eccb7ec454e6617738554a255d77f08e60ee0808 Patch Third Party Advisory
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rrfp-j2mp-hq9c Exploit Patch
https://github.com/tensorflow/tensorflow/issues/42105 Patch Third Party Advisory
Configurations

Configuration 1

cpe:2.3:a:google:tensorflow:*:*:*:*:-:*:*:*
Information

Published : 2020-10-21 09:15

Updated : 2021-08-17 01:21

NVD link : CVE-2020-15265

Mitre link : CVE-2020-15265

Products Affected
No products.
CWE
CWE-125

Out-of-bounds Read