CVE-2021-29536

LOW2.5EPSS 0.01%

Heap buffer overflow in `QuantizedReshape`

發布日:2021/5/21修改日:2026/3/13

描述

### Impact An attacker can cause a heap buffer overflow in `QuantizedReshape` by passing in invalid thresholds for the quantization: ```python import tensorflow as tf tensor = tf.constant([], dtype=tf.qint32) shape = tf.constant([], dtype=tf.int32) input_min = tf.constant([], dtype=tf.float32) input_max = tf.constant([], dtype=tf.float32) tf.raw_ops.QuantizedReshape(tensor=tensor, shape=shape, input_min=input_min, input_max=input_max) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/a324ac84e573fba362a5e53d4e74d5de6729933e/tensorflow/core/kernels/quantized_reshape_op.cc#L38-L55) assumes that the 2 arguments are always valid scalars and tries to access the numeric value directly: ```cc const auto& input_min_float_tensor = ctx->input(2); ... const float input_min_float = input_min_float_tensor.flat<float>()(0); const auto& input_max_float_tensor = ctx->input(3); ... const float input_max_float = input_max_float_tensor.flat<float>()(0); ``` However, if any of these tensors is empty, then `.flat<T>()` is an empty buffer and accessing the element at position 0 results in overflow. ### Patches We have patched the issue in GitHub commit [a324ac84e573fba362a5e53d4e74d5de6729933e](https://github.com/tensorflow/tensorflow/commit/a324ac84e573fba362a5e53d4e74d5de6729933e). 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 Ying Wang and Yakun Zhang of Baidu X-Team.

受影響套件(7)

  • Bitnami/tensorflowfrom 0, < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, >= 2.4.0, < 2.4.2
  • PyPI/tensorflowfrom 0, < 2.1.4
  • PyPI/tensorflowfrom 0, < a324ac84e573fba362a5e53d4e74d5de6729933e | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-cpufrom 0, < a324ac84e573fba362a5e53d4e74d5de6729933e | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-cpufrom 0, < 2.1.4
  • PyPI/tensorflow-gpufrom 0, < a324ac84e573fba362a5e53d4e74d5de6729933e | from 0, < 2.2.0rc0, >= 2.2.0, < 2.3.0rc0, >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-gpufrom 0, < 2.1.4

CVSS 分數

來源版本嚴重程度向量
osvCVSS 4.0—CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
osvCVSS 3.1LOW2.5CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

參考連結(7)