Memory exhaustion in Tensorflow
Medium4.3CVE-2022-21732 · Published Feb 10, 2022 · updated Sep 10, 2026
### Impact The [implementation of `ThreadPoolHandle`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135) can be used to trigger a denial of service attack by allocating too much memory: ```python import tensorflow as tf y = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name='tf') ``` This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. ### Patches We have patched the issue in GitHub commit [e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e](https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e). 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. ### 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 rep...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.5.3 | 2.5.3 |
| >= 2.6.0, < 2.6.3 | 2.6.3 | |
| >= 2.7.0, < 2.7.1 | 2.7.1 |
Details and references
### Impact The [implementation of `ThreadPoolHandle`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135) can be used to trigger a denial of service attack by allocating too much memory: ```python import tensorflow as tf y = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name='tf') ``` This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. ### Patches We have patched the issue in GitHub commit [e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e](https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e). 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. ### 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 Yu Tian of Qihoo 360 AIVul Team.
- CVSS 3.1
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-400, CWE-770
- Also known as
- BIT-tensorflow-2022-21732, CVE-2022-21732, PYSEC-2022-111, PYSEC-2022-56, PYSEC-2026-3158
- github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq
- nvd.nist.gov/vuln/detail/CVE-2022-21732
- github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-56.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-111.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135
More TensorFlow advisories
All TensorFlow| Date | Advisory | Severity | Fixed in |
|---|---|---|---|
| Feb 102022 | `CHECK`-failures in binary ops in Tensorflow | Medium6.5 | 2.5.3+2 more |
| Feb 102022 | `CHECK`-failures in `TensorByteSize` in Tensorflow | Medium6.5 | 2.5.3+2 more |
| Feb 102022 | `CHECK`-failures during Grappler's `SafeToRemoveIdentity` in Tensorflow | Medium6.5 | 2.5.3+2 more |
| Feb 102022 | Memory leak in Tensorflow | Medium4.3 | 2.5.3+2 more |
| Feb 102022 | Integer overflow in Tensorflow | High6.5 | 2.5.3+2 more |
| Feb 102022 | Integer overflow in Tensorflow | High6.5 | 2.5.3+2 more |