Vulnerability Information
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Vulnerability Title
Missing validation in shape inference for `Dequantize` in TensorFlow
Vulnerability Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
CVSS Information
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Vulnerability Type
输入验证不恰当
Vulnerability Title
Google TensorFlow 输入验证错误漏洞
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。 Google TensorFlow存在输入验证错误漏洞，该漏洞源于产品的 tf.raw_ops.Dequantize 未对输入的参数做有效验证，攻击者可通过该漏洞导致拒绝服务。以下产品及版本收到影响：TensorFlow 2.5.1、TensorFlow 2.4.3 和 TensorFlow 2.3.4。
CVSS Information
N/A
Vulnerability Type
N/A