CVE-2021-29531: CHECK-fail in tf.raw_ops.EncodePng
First published: Fri May 14 2021(Updated: )
### Impact An attacker can trigger a `CHECK` fail in PNG encoding by providing an empty input tensor as the pixel data: ```python import tensorflow as tf image = tf.zeros([0, 0, 3]) image = tf.cast(image, dtype=tf.uint8) tf.raw_ops.EncodePng(image=image) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L57-L60) only validates that the total number of pixels in the image does not overflow. Thus, an attacker can send an empty matrix for encoding. However, if the tensor is empty, then the associated buffer is `nullptr`. Hence, when [calling `png::WriteImageToBuffer`](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/kernels/image/encode_png_op.cc#L79-L93), the first argument (i.e., `image.flat<T>().data()`) is `NULL`. This then triggers the `CHECK_NOTNULL` in the [first line of `png::WriteImageToBuffer`](https://github.com/tensorflow/tensorflow/blob/e312e0791ce486a80c9d23110841525c6f7c3289/tensorflow/core/lib/png/png_io.cc#L345-L349). ```cc template <typename T> bool WriteImageToBuffer( const void* image, int width, int height, int row_bytes, int num_channels, int channel_bits, int compression, T* png_string, const std::vector<std::pair<std::string, std::string> >* metadata) { CHECK_NOTNULL(image); ... } ``` Since `image` is null, this results in `abort` being called after printing the stacktrace. Effectively, this allows an attacker to mount a denial of service attack. ### Patches We have patched the issue in GitHub commit [26eb323554ffccd173e8a79a8c05c15b685ae4d1](https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | <2.1.4 | |
| Google TensorFlow | >=2.2.0<2.2.3 | |
| Google TensorFlow | >=2.3.0<2.3.3 | |
| Google TensorFlow | >=2.4.0<2.4.2 | |
| pip/tensorflow-gpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-gpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-gpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-gpu | <2.1.4 | 2.1.4 |
| pip/tensorflow-cpu | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow-cpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-cpu | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow-cpu | <2.1.4 | 2.1.4 |
| pip/tensorflow | >=2.4.0<2.4.2 | 2.4.2 |
| pip/tensorflow | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow | >=2.2.0<2.2.3 | 2.2.3 |
| pip/tensorflow | <2.1.4 | 2.1.4 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf
- https://nvd.nist.gov/vuln/detail/CVE-2021-29531
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-459.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-657.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-168.yaml
- https://github.com/advisories/GHSA-3qxp-qjq7-w4hf (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-29531?
CVE-2021-29531 has a medium severity due to the potential for a CHECK failure in PNG encoding.
How do I fix CVE-2021-29531?
To resolve CVE-2021-29531, upgrade to TensorFlow version 2.4.2 or later.
Which versions of TensorFlow are affected by CVE-2021-29531?
CVE-2021-29531 affects TensorFlow versions up to 2.4.1, including 2.1.4, 2.2.x, and 2.3.x.
What kind of attacks can exploit CVE-2021-29531?
An attacker can exploit CVE-2021-29531 by providing an empty input tensor, causing a CHECK fail in PNG encoding.
Is there a workaround for CVE-2021-29531 if I cannot upgrade TensorFlow?
Currently, there is no documented workaround for CVE-2021-29531 other than upgrading to a patched version.
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