CVE-2021-29571 | Date: (C)2021-05-17 (M)2023-12-22 |
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 Score and Metrics +CVSS Score and Metrics -CVSS V3 Severity: | CVSS V2 Severity: |
CVSS Score : 7.8 | CVSS Score : 4.6 |
Exploit Score: 1.8 | Exploit Score: 3.9 |
Impact Score: 5.9 | Impact Score: 6.4 |
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CVSS V3 Metrics: | CVSS V2 Metrics: |
Attack Vector: LOCAL | Access Vector: LOCAL |
Attack Complexity: LOW | Access Complexity: LOW |
Privileges Required: LOW | Authentication: NONE |
User Interaction: NONE | Confidentiality: PARTIAL |
Scope: UNCHANGED | Integrity: PARTIAL |
Confidentiality: HIGH | Availability: PARTIAL |
Integrity: HIGH | |
Availability: HIGH | |
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