CVE-2024-9979 (GCVE-0-2024-9979)

Vulnerability from cvelistv5 – Published: 2024-10-15 14:01 – Updated: 2025-11-20 19:59
VLAI
Title
Pyo3: risk of use-after-free in `borrowed` reads from python weak references
Summary
A flaw was found in PyO3. This vulnerability causes a use-after-free issue, potentially leading to memory corruption or crashes via unsound borrowing from weak Python references.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-10-15 14:19 UTC
CWE
Assigner
redhat CNA under the redhat root
CNA scorecard B 82/100 over 1082 records in the last 180 days details
Impacted products
Vendor Product Version CPE status
Affected: 0.22.0 , < 0.22.4 (semver)
Red Hat Red Hat Ansible Automation Platform 2     cpe:/a:redhat:ansible_automation_platform:2
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Red Hat Red Hat Enterprise Linux 10     cpe:/o:redhat:enterprise_linux:10
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Red Hat Red Hat Enterprise Linux 8     cpe:/o:redhat:enterprise_linux:8
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Red Hat Red Hat Enterprise Linux 9     cpe:/o:redhat:enterprise_linux:9
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Date Public
2024-10-12 12:00
Show details on NVD website

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  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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Events included in the timeline

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    Related by attack behaviour

    Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.