Heap OOB in `FusedBatchNorm` kernels
Medium7.1CVE-2021-41223 · Published Nov 10, 2021 · updated Jul 8, 2026
### Impact The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/fused_batch_norm_op.cc#L1292) of `FusedBatchNorm` kernels is vulnerable to a heap OOB: ```python import tensorflow as tf tf.raw_ops.FusedBatchNormGrad( y_backprop=tf.constant([i for i in range(9)],shape=(1,1,3,3),dtype=tf.float32) x=tf.constant([i for i in range(2)],shape=(1,1,1,2),dtype=tf.float32) scale=[1,1], reserve_space_1=[1,1], reserve_space_2=[1,1,1], epsilon=1.0, data_format='NCHW', is_training=True) ``` ### Patches We have patched the issue in GitHub commit [aab9998916c2ffbd8f0592059fad352622f89cda](https://github.com/tensorflow/tensorflow/commit/aab9998916c2ffbd8f0592059fad352622f89cda). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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. ###...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | >= 2.6.0, < 2.6.1 | 2.6.1 |
| >= 2.5.0, < 2.5.2 | 2.5.2 | |
| < 2.4.4 | 2.4.4 |
Details and references
### Impact The [implementation](https://github.com/tensorflow/tensorflow/blob/e71b86d47f8bc1816bf54d7bddc4170e47670b97/tensorflow/core/kernels/fused_batch_norm_op.cc#L1292) of `FusedBatchNorm` kernels is vulnerable to a heap OOB: ```python import tensorflow as tf tf.raw_ops.FusedBatchNormGrad( y_backprop=tf.constant([i for i in range(9)],shape=(1,1,3,3),dtype=tf.float32) x=tf.constant([i for i in range(2)],shape=(1,1,1,2),dtype=tf.float32) scale=[1,1], reserve_space_1=[1,1], reserve_space_2=[1,1,1], epsilon=1.0, data_format='NCHW', is_training=True) ``` ### Patches We have patched the issue in GitHub commit [aab9998916c2ffbd8f0592059fad352622f89cda](https://github.com/tensorflow/tensorflow/commit/aab9998916c2ffbd8f0592059fad352622f89cda). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-125
- Also known as
- BIT-tensorflow-2021-41223, CVE-2021-41223, PYSEC-2021-415, PYSEC-2021-632, PYSEC-2021-830
- github.com/tensorflow/tensorflow/security/advisories/GHSA-f54p-f6jp-4rhr
- nvd.nist.gov/vuln/detail/CVE-2021-41223
- github.com/tensorflow/tensorflow/commit/aab9998916c2ffbd8f0592059fad352622f89cda
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-632.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-830.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-415.yaml
- github.com/tensorflow/tensorflow
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