GitHub Advisoryadvisory · PyPI

GHSA-jhq9-wm9m-cf89 CHECK-failure in `UnsortedSegmentJoin`

LOW Published 2021-05-21 Modified 2024-10-31 Official page ↗
Aliases
CVE-2021-29552
Ecosystem
PyPI
Packages
tensorflow, tensorflow-cpu, tensorflow-gpu
Severity
Low
CVSS vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Weaknesses
CWE-617
Reviewed
2021-05-18

Affected packages

• PyPI tensorflow: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow: >= 2.4.0, < 2.4.2 → fixed in 2.4.2 • PyPI tensorflow-cpu: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow-cpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow-cpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow-cpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2 • PyPI tensorflow-gpu: < 2.1.4 → fixed in 2.1.4 • PyPI tensorflow-gpu: >= 2.2.0, < 2.2.3 → fixed in 2.2.3 • PyPI tensorflow-gpu: >= 2.3.0, < 2.3.3 → fixed in 2.3.3 • PyPI tensorflow-gpu: >= 2.4.0, < 2.4.2 → fixed in 2.4.2

Description

Impact An attacker can cause a denial of service by controlling the values of `num_segments` tensor argument for `UnsortedSegmentJoin`: ```python import tensorflow as tf inputs = tf.constant([], dtype=tf.string) segment_ids = tf.constant([], dtype=tf.int32) num_segments = tf.constant([], dtype=tf.int32) separator = '' tf.raw_ops.UnsortedSegmentJoin( inputs=inputs, segment_ids=segment_ids, num_segments=num_segments, separator=separator) ``` This is because the implementation assumes that the `num_segments` tensor is a valid scalar: ```cc const Tensor& num_segments_tensor = context->input(2); auto num_segments = num_segments_tensor.scalar()(); ``` Since the tensor is empty the `CHECK` involved in `.scalar()()` that checks that the number of elements is exactly 1 will be invalidated and this would result in process termination. Patches We have patched the issue in GitHub commit 704866eabe03a9aeda044ec91a8d0c83fc1ebdbe. 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 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.

Related

Alias · CVE (1)

  • CVE-2021-29552 TensorFlow is an end-to-end open source platform for machine learning. vulnerability

Weakness · CWE (1)

  • CWE-617 Reachable Assertion weakness

References