CVE-2021-29569 – tensorflow-gpu

Package

Manager: pip
Name: tensorflow-gpu
Vulnerable Version: >=0 <2.1.4 || >=2.2.0 <2.2.3 || >=2.3.0 <2.3.3 || >=2.4.0 <2.4.2

Severity

Level: Low

CVSS v3.1: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

CVSS v4.0: CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

EPSS: 0.00017 pctl0.02747

Details

Heap out of bounds read in `RequantizationRange` ### Impact The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs: ```python import tensorflow as tf input = tf.constant([1], shape=[1], dtype=tf.qint32) input_max = tf.constant([], dtype=tf.float32) input_min = tf.constant([], dtype=tf.float32) tf.raw_ops.RequantizationRange(input=input, input_min=input_min, input_max=input_max) ``` 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: ```cc const float input_min_float = ctx->input(1).flat<float>()(0); const float input_max_float = ctx->input(2).flat<float>()(0); ``` 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. ### Patches We have patched the issue in GitHub commit [ef0c008ee84bad91ec6725ddc42091e19a30cf0e](https://github.com/tensorflow/tensorflow/commit/ef0c008ee84bad91ec6725ddc42091e19a30cf0e). 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. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Ying Wang and Yakun Zhang of Baidu X-Team.

Metadata

Created: 2021-05-21T14:25:22Z
Modified: 2024-11-01T17:05:44Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2021/05/GHSA-3h8m-483j-7xxm/GHSA-3h8m-483j-7xxm.json
CWE IDs: ["CWE-125"]
Alternative ID: GHSA-3h8m-483j-7xxm
Finding: F111
Auto approve: 1