CVE-2022-21732

Memory exhaustion in Tensorflow

Published Feb 3, 2022 CVSS 3.1 · 4.3 Medium EPSS < 1% KEV · Not listed
Description
Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Analysis

No analysis available yet

Remediation

No remediation available yet

Tracking

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Advisories

Source ID Title
EUVD EUVD EUVD-2022-0295 Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.
Github GHSA Github GHSA GHSA-c582-c96p-r5cq Memory exhaustion in Tensorflow
History
Type Values Removed Values Added
Metrics ssvc

{'options': {'Automatable': 'no', 'Exploitation': 'none', 'Technical Impact': 'partial'}, 'version': '2.0.3'}

Weaknesses
  • CWE-770

    Allocation of Resources Without Limits or Throttling

Sources

Status
PUBLISHED
Assigner
GitHub_M
Published
Updated
Feb 12, 2025, 3:58 PM
Reserved
Nov 16, 2021, 12:00 AM
Status
Modified
Published
Feb 3, 2022, 12:15 PM
Modified
Jun 17, 2026, 4:26 AM