发布时间: 2022年8月11日
修改时间: 2022年8月11日
Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don t match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
| NVD | openEuler | |
|---|---|---|
| CVSS评分 | 6.5 | 6.5 |
| Attack Vector | Network | Network |
| Attack Complexity | Low | Low |
| Privileges Required | Low | Low |
| User Interaction | None | None |
| Scope | Unchanged | Unchanged |
| Confidentiality | None | None |
| Integrity | None | None |
| Availability | High | High |
| 公告名 | 概要 | 发布时间 |
|---|---|---|
| KylinSec-SA-2022-1872 | Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that any binary op would trigger `CHECK` failures. This occurs when the protobuf part corresponding to the tensor arguments is modified such that the `dtype` no longer matches the `dtype` expected by the op. In that case, calling the templated binary operator for the binary op would receive corrupted data, due to the type confusion involved. If `Tin` and `Tout` don t match the type of data in `out` and `input_*` tensors then `flat<*>` would interpret it wrongly. In most cases, this would be a silent failure, but we have noticed scenarios where this results in a `CHECK` crash, hence a denial of service. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. | 2022年8月11日 |
| 产品 | 包 | 状态 |
|---|---|---|
| KY3.4-4A | tensorflow | Unaffected |
| KY3.4-5 | tensorflow | Unaffected |
| KY3.5.1 | tensorflow | Unaffected |
