Описание
CHECK-fail in LoadAndRemapMatrix
Impact
An attacker can cause a denial of service by exploiting a CHECK-failure coming from tf.raw_ops.LoadAndRemapMatrix:
This is because the implementation assumes that the ckpt_path is always a valid scalar.
However, an attacker can send any other tensor as the first argument of LoadAndRemapMatrix. This would cause the rank CHECK in scalar<T>()() to trigger and terminate the process.
Patches
We have patched the issue in GitHub commit 77dd114513d7796e1e2b8aece214a380af26fbf4.
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.
Ссылки
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gvm4-h8j3-rjrq
- https://nvd.nist.gov/vuln/detail/CVE-2021-29561
- https://github.com/tensorflow/tensorflow/commit/77dd114513d7796e1e2b8aece214a380af26fbf4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-489.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-687.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-198.yaml
Пакеты
tensorflow
< 2.1.4
2.1.4
tensorflow
>= 2.2.0, < 2.2.3
2.2.3
tensorflow
>= 2.3.0, < 2.3.3
2.3.3
tensorflow
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-cpu
< 2.1.4
2.1.4
tensorflow-cpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-cpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-cpu
>= 2.4.0, < 2.4.2
2.4.2
tensorflow-gpu
< 2.1.4
2.1.4
tensorflow-gpu
>= 2.2.0, < 2.2.3
2.2.3
tensorflow-gpu
>= 2.3.0, < 2.3.3
2.3.3
tensorflow-gpu
>= 2.4.0, < 2.4.2
2.4.2
Связанные уязвимости
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from `tf.raw_ops.LoadAndRemapMatrix`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/d94227d43aa125ad8b54115c03cece54f6a1977b/tensorflow/core/kernels/ragged_tensor_to_tensor_op.cc#L219-L222) assumes that the `ckpt_path` is always a valid scalar. However, an attacker can send any other tensor as the first argument of `LoadAndRemapMatrix`. This would cause the rank `CHECK` in `scalar<T>()()` to trigger and terminate the process. 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.
TensorFlow is an end-to-end open source platform for machine learning. ...