Safety vulnerability ID: 40470
The information on this page was manually curated by our Cybersecurity Intelligence Team.
Tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2, and 2.5.0 include a fix for CVE-2021-29571: 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.
Latest version: 2.16.1
TensorFlow is an open source machine learning framework for everyone.
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. See CVE-2021-29571.
CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-whr9-vfh2-7hm6
MISC:https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517: https://github.com/tensorflow/tensorflow/commit/79865b542f9ffdc9caeb255631f7c56f1d4b6517
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