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CVE-2023-2163 (GCVE-0-2023-2163)

Vulnerability from cvelistv5 – Published: 2023-09-20 05:02 – Updated: 2025-02-27 20:49
VLAI
Title
Incorrect Verifier Branch Pruning Logic Leads To Arbitrary Read/Write In Linux Kernel and Lateral Privilege Escalation
Summary
Incorrect verifier pruning in BPF in Linux Kernel >=5.4 leads to unsafe code paths being incorrectly marked as safe, resulting in arbitrary read/write in kernel memory, lateral privilege escalation, and container escape.
Severity
10 (Critical)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:N
SSVC
Exploitation: none Automatable: yes Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-26 21:50 UTC
CWE
Assigner
References
Impacted products
Vendor Product Version CPE status
Linux Linux Kernel Unaffected: 0 , < 5.4 (custom)
Affected: 0 , < 71b547f561247897a0a14f3082730156c0533fed (git)
guessed Create a notification for this product.
Show details on NVD website
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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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.


Detection rules are retrieved from Rulezet.


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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.