漏洞信息
尽管我们使用了先进的大模型技术，但其输出仍可能包含不准确或过时的信息。神龙努力确保数据的准确性，但请您根据实际情况进行核实和判断。
Vulnerability Title
Division by 0 in `QuantizedBatchNormWithGlobalNormalization`
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/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the op's contract(https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization). 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存在数字错误漏洞，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