Vulnerability Information
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Vulnerability Title
Heap out of bounds in `QuantizedBatchNormWithGlobalNormalization`
Vulnerability Description
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds 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#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. 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
跨界内存读
Vulnerability Title
Google TensorFlow 缓冲区错误漏洞
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存在缓冲区错误漏洞，攻击者可利用该漏洞可以通过访问tf.raw_ops.QuantizedBatchNormWithGlobalNormalization中边界以外的数据来导致段错误和拒绝服务。
CVSS Information
N/A
Vulnerability Type
N/A