Memory corruption in Tensorflow
High7.1CVE-2020-15193 · Published Sep 25, 2020 · updated Jul 8, 2026
### Impact The implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/tfe_wrapper.cc#L1361 However, there is nothing stopping users from passing in a Python object instead of a tensor. ```python In [2]: tf.experimental.dlpack.to_dlpack([2]) ==1720623==WARNING: MemorySanitizer: use-of-uninitialized-value #0 0x55b0ba5c410a in tensorflow::(anonymous namespace)::GetTensorFromHandle(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:46:7 #1 0x55b0ba5c38f4 in tensorflow::TFE_HandleToDLPack(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:252:26 ... ``` The uninitialized memory address is due to a `reinterpret_cast` https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/eager/pywrap_tensor.cc#L848-L850 Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. ### Patches We have patched the issue in 22e0...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | >= 2.2.0, < 2.2.1 | 2.2.1 |
| >= 2.3.0, < 2.3.1 | 2.3.1 |
Details and references
### Impact The implementation of `dlpack.to_dlpack` can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/tfe_wrapper.cc#L1361 However, there is nothing stopping users from passing in a Python object instead of a tensor. ```python In [2]: tf.experimental.dlpack.to_dlpack([2]) ==1720623==WARNING: MemorySanitizer: use-of-uninitialized-value #0 0x55b0ba5c410a in tensorflow::(anonymous namespace)::GetTensorFromHandle(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:46:7 #1 0x55b0ba5c38f4 in tensorflow::TFE_HandleToDLPack(TFE_TensorHandle*, TF_Status*) third_party/tensorflow/c/eager/dlpack.cc:252:26 ... ``` The uninitialized memory address is due to a `reinterpret_cast` https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/python/eager/pywrap_tensor.cc#L848-L850 Since the `PyObject` is a Python object, not a TensorFlow Tensor, the cast to `EagerTensor` fails. ### Patches We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions. We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
- CVSS 3.1
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-908
- Also known as
- BIT-tensorflow-2020-15193, CVE-2020-15193, PYSEC-2020-116, PYSEC-2020-273, PYSEC-2020-308
- github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v
- nvd.nist.gov/vuln/detail/CVE-2020-15193
- github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-273.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-308.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-116.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
More TensorFlow advisories
All TensorFlow| Date | Advisory | Severity | Fixed in |
|---|---|---|---|
| Sep 252020 | Out of bounds access in tensorflow-lite | Critical8.1 | 2.2.1+1 more |
| Sep 252020 | Out of bounds write in tensorflow-lite | Critical8.1 | 2.2.1+1 more |
| Sep 252020 | Denial of service in tensorflow-lite | Medium4.0 | 2.2.1+1 more |
| Sep 252020 | Segmentation fault in tensorflow-lite | High6.5 | 1.15.4+4 more |
| Sep 252020 | Out of bounds access in tensorflow-lite | Medium4.8 | 1.15.4+4 more |
| Sep 252020 | Null pointer dereference in tensorflow-lite | High5.9 | 1.15.4+4 more |