Vulnerability Information
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Vulnerability Title
Division by 0 in `QuantizedAdd`
Vulnerability 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.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.
CVSS Information
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Vulnerability Type
除零错误
Vulnerability Title
Google TensorFlow 数字错误漏洞
Vulnerability Description
Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 TensorFlow 2.4.2,2.3.3,2.2.3，2.1.4存在安全漏洞，攻击者可利用该漏洞可以导致tf.raw_ops.QuantizedBatchNormWithGlobalNormalization中的运行时除零错误和拒绝服务。
CVSS Information
N/A
Vulnerability Type
N/A