CVE-2021-29569 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/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.ccL49-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.

CVSS Vector

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H

Reference

https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e

Attack Complexity

LOW

Privileges Required

LOW

User Interaction Required

LOW

Scope

NONE

Confidentiality Impact

UNCHANGED

Integrity Impact

HIGH

Availability Impact

NONE

Base Score

HIGH

Base Severity

7.1