Vulnerability Information
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Vulnerability Title
Memory corruption in `DrawBoundingBoxesV2`
Vulnerability Description
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/31bd5026304677faa8a0b77602c6154171b9aec1/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L116-L130) assumes that the last element of `boxes` input is 4, as required by [the op](https://www.tensorflow.org/api_docs/python/tf/raw_ops/DrawBoundingBoxesV2). Since this is not checked attackers passing values less than 4 can write outside of bounds of heap allocated objects and cause memory corruption. If the last dimension in `boxes` is less than 4, accesses similar to `tboxes(b, bb, 3)` will access data outside of bounds. Further during code execution there are also writes to these indices. 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.
CVSS Information
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:L/I:L/A:L
Vulnerability Type
跨界内存写
Vulnerability Title
Google TensorFlow 缓冲区错误漏洞
Vulnerability Description
Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 TensorFlow 2.4.2,2.3.3,2.2.3，2.1.4存在缓冲区错误漏洞，该漏洞源于攻击者提供了特殊的输入，tf.raw_ops.MaxPoolGradWithArgmax可能导致读取超出堆分配数据的边界。
CVSS Information
N/A
Vulnerability Type
N/A