CVE-2021-37639: Null pointer dereference and heap OOB read in TensorFlow
First published: Thu Aug 12 2021(Updated: )
### Impact When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer: ```python import tensorflow as tf tf.raw_ops.Restore( file_pattern=['/tmp'], tensor_name=[], default_value=21, dt=tf.int, preferred_shard=1) ``` The same undefined behavior can be triggered by `tf.raw_ops.RestoreSlice`: ```python import tensorflow as tf tf.raw_ops.RestoreSlice( file_pattern=['/tmp'], tensor_name=[], shape_and_slice='2', dt=inp.array([tf.int]), preferred_shard=1) ``` Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration: ```python import tensorflow as tf tf.raw_ops.Restore( file_pattern=['/tmp'], tensor_name=['x'], default_value=21, dt=tf.int, preferred_shard=42) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/47a06f40411a69c99f381495f490536972152ac0/tensorflow/core/kernels/save_restore_tensor.cc#L158-L159) retrieves the tensor list corresponding to the `tensor_name` user controlled input and immediately retrieves the tensor at the restoration index (controlled via `preferred_shard` argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read. ### Patches We have patched the issue in GitHub commit [9e82dce6e6bd1f36a57e08fa85af213e2b2f2622](https://github.com/tensorflow/tensorflow/commit/9e82dce6e6bd1f36a57e08fa85af213e2b2f2622). 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.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/tensorflow-gpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-gpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-gpu | <2.3.4 | 2.3.4 |
| pip/tensorflow-cpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-cpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-cpu | <2.3.4 | 2.3.4 |
| pip/tensorflow | =2.5.0 | 2.5.1 |
| pip/tensorflow | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow | <2.3.4 | 2.3.4 |
| TensorFlow Keras | >=2.3.0<2.3.4 | |
| TensorFlow Keras | >=2.4.0<2.4.3 | |
| TensorFlow Keras | =2.5.0 | |
| TensorFlow Keras | =2.6.0-rc0 | |
| TensorFlow Keras | =2.6.0-rc1 | |
| TensorFlow Keras | =2.6.0-rc2 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/9e82dce6e6bd1f36a57e08fa85af213e2b2f2622
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gh6x-4whr-2qv4
- https://nvd.nist.gov/vuln/detail/CVE-2021-37639
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-552.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-750.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-261.yaml
- https://github.com/advisories/GHSA-gh6x-4whr-2qv4 (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-37639?
CVE-2021-37639 has a medium severity rating as it can lead to a denial of service due to a null pointer dereference.
What versions of TensorFlow are affected by CVE-2021-37639?
CVE-2021-37639 affects TensorFlow versions 2.3.0 to 2.3.4, 2.4.0 to 2.4.3, and specific release candidates of 2.6.0.
How do I fix CVE-2021-37639?
To fix CVE-2021-37639, upgrade TensorFlow to version 2.5.1 or later.
Can CVE-2021-37639 be exploited remotely?
Yes, CVE-2021-37639 can potentially be exploited remotely if untrusted inputs are processed.
What is the impact of CVE-2021-37639 on TensorFlow applications?
The impact of CVE-2021-37639 on TensorFlow applications can result in crashes or unexpected behavior due to the null pointer dereference.
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