CVEvulnerability

CVE-2021-29569

7.1 HIGH Published 2021-05-14 Modified 2026-06-17 Official page ↗
Status
Modified
Published
2021-05-14
Last modified
2026-06-17
Assigner
[email protected]
CVSS 3.1 ([email protected])
2.5 LOW — CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
CVSS 3.1 ([email protected])
7.1 HIGH — CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
CVSS 2.0 ([email protected])
3.6 LOW — AV:L/AC:L/Au:N/C:P/I:N/A:P
Weaknesses
CWE-125

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/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. 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.

Affected configurations

• google tensorflow (< 2.1.4) • google tensorflow (>= 2.2.0 < 2.2.3) • google tensorflow (>= 2.3.0 < 2.3.3) • google tensorflow (>= 2.4.0 < 2.4.2)

Related

Weakness · CWE (1)

  • CWE-125 Out-of-bounds Read weakness

References