CVE-2021-29549
Assigner: GitHub_M
Published: 2021-05-14T19:10:41
State: PUBLISHED
affected: product: tensorflow
vendor: tensorflow
versions: status: affected
version: < 2.1.4
status: affected
version: >= 2.2.0, < 2.2.3
status: affected
version: >= 2.3.0, < 2.3.3
status: affected
version: >= 2.4.0, < 2.4.2
descriptions: value: 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.cc#L289-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.cc#L522-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.
metrics: cvssV3_1: attackComplexity: HIGH
attackVector: LOCAL
availabilityImpact: LOW
baseScore: 2.5
baseSeverity: LOW
confidentialityImpact: NONE
integrityImpact: NONE
privilegesRequired: LOW
scope: UNCHANGED
userInteraction: NONE
vectorString: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
version: 3.1
problemTypes: descriptions: cweId: CWE-369
description: CWE-369: Divide By Zero
type: CWE
source: advisory: GHSA-x83m-p7pv-ch8v
discovery: UNKNOWN
title: Division by 0 in `QuantizedAdd`