GitHub Advisoryadvisory · PyPI

GHSA-r4c4-5fpq-56wg Heap OOB in boosted trees

HIGH Published 2021-08-25 Modified 2024-11-13 Official page ↗
Aliases
CVE-2021-37664
Ecosystem
PyPI
Packages
tensorflow, tensorflow-cpu, tensorflow-gpu
Severity
High
CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H
Weaknesses
CWE-125
Reviewed
2021-08-24

Affected packages

• PyPI tensorflow: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-cpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-cpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-cpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1 • PyPI tensorflow-gpu: < 2.3.4 → fixed in 2.3.4 • PyPI tensorflow-gpu: >= 2.4.0, < 2.4.3 → fixed in 2.4.3 • PyPI tensorflow-gpu: >= 2.5.0, < 2.5.1 → fixed in 2.5.1

Description

Impact An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to `BoostedTreesSparseCalculateBestFeatureSplit`: ```python import tensorflow as tf tf.raw_ops.BoostedTreesSparseCalculateBestFeatureSplit( node_id_range=[0,10], stats_summary_indices=[[1, 2, 3, 0x1000000]], stats_summary_values=[1.0], stats_summary_shape=[1,1,1,1], l1=l2=[1.0], tree_complexity=[0.5], min_node_weight=[1.0], logits_dimension=3, split_type='inequality') ``` The implementation needs to validate that each value in `stats_summary_indices` is in range. Patches We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 members of the Aivul Team from Qihoo 360.

Related

Alias · CVE (1)

  • CVE-2021-37664 TensorFlow is an end-to-end open source platform for machine learning. vulnerability

Weakness · CWE (1)

  • CWE-125 Out-of-bounds Read weakness

References