Advisoriesby IbisHeap OOB in `ResourceScatterUpdate`
Impact
An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to tf.raw_ops.ResourceScatterUpdate:
```python
import tensorflow as tf
v = tf.Variable([b'vvv'])
tf.raw_ops.ResourceScatterUpdate(
resource=v.handle,
indices=[0],
updates=['1', '2', '3', '4', '5'])
`
The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of indices and updates: instead of checking that the shape of indices is a prefix of the shape of updates (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship.
Patches
We have patched the issue in GitHub commit [01cff3f986259d661103412a20745928c727326f](https://github.com/tensorflow/tensorflow/commit/01cff3f986259d661103412a20745928c727326f).
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.
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...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.3.4 | 2.3.4 |
| >= 2.4.0, < 2.4.3 | 2.4.3 | |
| >= 2.5.0, < 2.5.1 | 2.5.1 |
Details and references
### Impact An attacker can trigger a read from outside of bounds of heap allocated data by sending invalid arguments to `tf.raw_ops.ResourceScatterUpdate`: ```python import tensorflow as tf v = tf.Variable([b'vvv']) tf.raw_ops.ResourceScatterUpdate( resource=v.handle, indices=[0], updates=['1', '2', '3', '4', '5']) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L919-L923) has an incomplete validation of the relationship between the shapes of `indices` and `updates`: instead of checking that the shape of `indices` is a prefix of the shape of `updates` (so that broadcasting can happen), code only checks that the number of elements in these two tensors are in a divisibility relationship. ### Patches We have patched the issue in GitHub commit [01cff3f986259d661103412a20745928c727326f](https://github.com/tensorflow/tensorflow/commit/01cff3f986259d661103412a20745928c727326f). 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. ### 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:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-125
- Also known as
- BIT-tensorflow-2021-37655, CVE-2021-37655, PYSEC-2021-277, PYSEC-2021-568, PYSEC-2021-766
- github.com/tensorflow/tensorflow/security/advisories/GHSA-7fvx-3jfc-2cpc
- nvd.nist.gov/vuln/detail/CVE-2021-37655
- github.com/tensorflow/tensorflow/commit/01cff3f986259d661103412a20745928c727326f
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-568.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-766.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-277.yaml
- github.com/tensorflow/tensorflow
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