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CVE-2022-29197

MEDIUM
Published 2022-05-20T21:55:18.000Z
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CVSS Score

V3.1
5.5
/10
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.001
probability
of exploitation in the wild

There is a 0.1% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.303
Higher than 30.3% of all CVEs

Attack Vector Metrics

Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
NONE
Integrity
NONE
Availability
HIGH

Description

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Understanding This Vulnerability

This Common Vulnerabilities and Exposures (CVE) entry provides detailed information about a security vulnerability that has been publicly disclosed. CVEs are standardized identifiers assigned by MITRE Corporation to track and catalog security vulnerabilities across software and hardware products.

The severity rating (MEDIUM) indicates the potential impact of this vulnerability based on the CVSS (Common Vulnerability Scoring System) framework. Higher severity ratings typically indicate vulnerabilities that could lead to more significant security breaches if exploited. Security teams should prioritize remediation efforts based on severity, exploit availability, and the EPSS (Exploit Prediction Scoring System) score, which predicts the likelihood of exploitation in the wild.

If this vulnerability affects products or systems in your infrastructure, we recommend reviewing the affected products section, checking for available patches or updates from vendors, and implementing recommended workarounds or solutions until a permanent fix is available. Organizations should also monitor security advisories and threat intelligence feeds for updates about active exploitation of this vulnerability.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

References

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed MODERATE

Missing validation causes denial of service via `UnsortedSegmentJoin`

GHSA-hrg5-737c-2p56

Advisory Details

### Impact The implementation of [`tf.raw_ops.UnsortedSegmentJoin`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L95) 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 tf.raw_ops.UnsortedSegmentJoin( inputs=tf.constant("this", shape=[12], dtype=tf.string), segment_ids=tf.constant(0, shape=[12], dtype=tf.int64), num_segments=tf.constant(0, shape=[12], dtype=tf.int64)) ``` The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value: ```cc const Tensor& num_segments_tensor = context->input(2); OP_REQUIRES(context, num_segments_tensor.NumElements() != 0, errors::InvalidArgument("Number of segments cannot be empty.")); auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()(); ``` ### Patches We have patched the issue in GitHub commit [13d38a07ce9143e044aa737cfd7bb759d0e9b400](https://github.com/tensorflow/tensorflow/commit/13d38a07ce9143e044aa737cfd7bb759d0e9b400). 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](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 Neophytos Christou from Secure Systems Lab at Brown University.

Affected Packages

PyPI tensorflow
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥0 <2.6.4
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.7.0 <2.7.2
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.8.0 <2.8.1

CVSS Scoring

CVSS Score

5.0

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: May 24, 2022, Modified: May 24, 2022

References

Published: 2022-05-20T21:55:18.000Z
Last Modified: 2025-04-22T17:59:07.613Z
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