GHSA-3qxp-qjq7-w4hf

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    GHSA-3qxp-qjq7-w4hf

    Published: 21 May 2021Last Modified: 8 Jul 2026

    Summary: CHECK-fail in tf.raw_ops.EncodePng

    Details: ### 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.

    Affected packages

    Package

    Name: tensorflow

    Purl: pkg:pypi/tensorflow

    Affected ranges

    Type: ECOSYSTEM

    Events:

    Introduced- 0
    Fixed -2.1.4

    Affected versions

    0.12.0
    0.12.1

    Common Vulnerability Scoring System

    Attack Vector
    Network
    Adjacent
    Local
    Physical
    Privileges Required
    None
    Low
    High
    User Interaction
    None
    Required
    Scope
    Unchanged
    Changed
    Confidentiality
    None
    Low
    High
    Integrity
    None
    Low
    High
    Availability
    None
    Low
    High
    GHSA-3qxp-qjq7-w4hf | CVE-DB