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CVE-2023-2235 (GCVE-0-2023-2235)

Vulnerability from cvelistv5 – Published: 2023-05-01 12:51 – Updated: 2026-08-07 18:47
VLAI
Title
Use-after-free in Linux kernel's Performance Events subsystem
Summary
A use-after-free vulnerability in the Linux Kernel Performance Events system can be exploited to achieve local privilege escalation. The perf_group_detach function did not check the event's siblings' attach_state before calling add_event_to_groups(), but remove_on_exec made it possible to call list_del_event() on before detaching from their group, making it possible to use a dangling pointer causing a use-after-free vulnerability. We recommend upgrading past commit fd0815f632c24878e325821943edccc7fde947a2.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-03-05 18:38 UTC
CWE
Impacted products
Vendor Product Version CPE status
Linux Linux Kernel Affected: 5.13 , < 6.3 (custom)
guessed Create a notification for this product.
Date Public
2023-03-15 20:49
Show details on NVD website

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Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • 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.

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Detection rules are retrieved from Rulezet.

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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.


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