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CVE-2022-2319 (GCVE-0-2022-2319)

Vulnerability from cvelistv5 – Published: 2022-09-01 00:00 – Updated: 2024-08-03 00:32
VLAI
Summary
A flaw was found in the Xorg-x11-server. An out-of-bounds access issue can occur in the ProcXkbSetGeometry function due to improper validation of the request length.
CWE
Impacted products
Vendor Product Version CPE status
n/a xorg-x11-server Affected: xorg-x11-server 21.1
Show details on NVD website

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    "redhat_vex": {
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      "current_release_date": "2025-11-21T11:09:47+00:00",
      "cve": "CVE-2022-2319",
      "id": "CVE-2022-2319",
      "initial_release_date": "2022-07-13T00:00:00+00:00",
      "product_status:fixed": "570",
      "product_status:known_affected": "9",
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      "title": "xorg-x11-server: X.Org Server ProcXkbSetGeometry out-of-bounds access",
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      "cve": "CVE-2022-2319",
      "id": "CVE-2022-2319",
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      "product_status:recommended": "269",
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      "status": "interim",
      "title": "SUSE CVE CVE-2022-2319",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2022-2319.json",
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  }
}



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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.
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  • 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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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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