CHECK-fail in tf.raw_ops.EncodePng

### 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.

CVSS 3.1

CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

Severity from

GitHub (reviewed advisory)

Weakness

CWE-754

Also known as

BIT-tensorflow-2021-29531, CVE-2021-29531, PYSEC-2021-168, PYSEC-2021-459, PYSEC-2021-657

• github.com/tensorflow/tensorflow/security/advisories/GHSA-3qxp-qjq7-w4hf
• nvd.nist.gov/vuln/detail/CVE-2021-29531
• github.com/tensorflow/tensorflow/commit/26eb323554ffccd173e8a79a8c05c15b685ae4d1
• github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-459.yaml
• github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-657.yaml
• github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-168.yaml
• github.com/tensorflow/tensorflow