CVE编号
CVE-2021-37677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 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.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/da857cfa0fde8f79ad0afdbc94e88... | |
| https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh26 |
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 | tensorflow | * |
From (including) 2.3.0 |
Up to (excluding) 2.3.4 |
|||||
| 运行在以下环境 | |||||||||
| 应用 | tensorflow | * |
From (including) 2.4.0 |
Up to (excluding) 2.4.3 |
|||||
| 运行在以下环境 | |||||||||
| 应用 | tensorflow | 2.5.0 | - | ||||||
| 运行在以下环境 | |||||||||
| 应用 | tensorflow | 2.6.0 | - | ||||||
- 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 无
- 完整性 无
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