Upstream information
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.SUSE information
Overall state of this security issue: Does not affect SUSE products
This issue is currently rated as having important severity.
National Vulnerability Database | |
---|---|
Base Score | 4.6 |
Vector | AV:L/AC:L/Au:N/C:P/I:P/A:P |
Access Vector | Local |
Access Complexity | Low |
Authentication | None |
Confidentiality Impact | Partial |
Integrity Impact | Partial |
Availability Impact | Partial |
National Vulnerability Database | |
---|---|
Base Score | 7.8 |
Vector | CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H |
Attack Vector | Local |
Attack Complexity | Low |
Privileges Required | Low |
User Interaction | None |
Scope | Unchanged |
Confidentiality Impact | High |
Integrity Impact | High |
Availability Impact | High |
CVSSv3 Version | 3.1 |
SUSE Timeline for this CVE
CVE page created: Mon May 17 08:58:28 2021CVE page last modified: Sat Mar 30 16:29:52 2024