CVE-2021-29549 Information

Jun 07, 2022 cve

Description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.ccL289-L295) computes a modulo operation without validating that the divisor is not zero. Since vector_num_elements is determined based on input shapes(https://github.com/tensorflow/tensorflow/blob/6f26b3f3418201479c264f2a02000880d8df151c/tensorflow/core/kernels/quantized_add_op.ccL522-L544) a user can trigger scenarios where this quantity is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 TensorFlow 2.3.3 TensorFlow 2.2.3 and TensorFlow 2.1.4 as these are also affected and still in supported range.

CVSS Vector

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

Reference

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x83m-p7pv-ch8v https://github.com/tensorflow/tensorflow/commit/744009c9e5cc5d0447f0dc39d055f917e1fd9e16

Attack Complexity

LOW

Privileges Required

LOW

User Interaction Required

LOW

Scope

NONE

Confidentiality Impact

UNCHANGED

Integrity Impact

NONE

Availability Impact

NONE

Base Score

HIGH

Base Severity

5.5

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