google tensorflow 数值类型间的不正确转换

CVE编号

CVE-2021-37679

利用情况

暂无

补丁情况

N/A

披露时间

2021-08-13

漏洞描述

TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a `tf.map_fn` within another `tf.map_fn` call. However, if the input tensor is a `RaggedTensor` and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The `t` and `z` outputs should be identical, however this is not the case. The last row of `t` contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a `Variant` tensor to a `RaggedTensor`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/ragged_tensor_from_variant_op.cc#L177-L190) does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. 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.

解决建议

建议您更新当前系统或软件至最新版，完成漏洞的修复。

参考链接
https://github.com/tensorflow/tensorflow/commit/4e2565483d0ffcadc719bd44893fb...
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g8wg-cjwc-xhhp

受影响软件情况

#	类型	厂商	产品	版本	影响面
1
	运行在以下环境
	应用	google	tensorflow	*	From (including) 2.3.0	Up to (excluding) 2.3.4
	运行在以下环境
	应用	google	tensorflow	*	From (including) 2.4.0	Up to (excluding) 2.4.3
	运行在以下环境
	应用	google	tensorflow	2.5.0	-
	运行在以下环境
	应用	google	tensorflow	2.6.0	-

CVSS3评分 7.8

• 攻击路径 本地
• 攻击复杂度 低
• 权限要求 低
• 影响范围 未更改
• 用户交互 无
• 可用性 高
• 保密性 高
• 完整性 高

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H CWE-ID 漏洞类型 CWE-681 数值类型间的不正确转换