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CVE-2023-52509 (GCVE-0-2023-52509)

Vulnerability from cvelistv5 – Published: 2024-03-02 21:52 – Updated: 2026-08-05 09:10
VLAI
Title
ravb: Fix use-after-free issue in ravb_tx_timeout_work()
Summary
In the Linux kernel, the following vulnerability has been resolved: ravb: Fix use-after-free issue in ravb_tx_timeout_work() The ravb_stop() should call cancel_work_sync(). Otherwise, ravb_tx_timeout_work() is possible to use the freed priv after ravb_remove() was called like below: CPU0 CPU1 ravb_tx_timeout() ravb_remove() unregister_netdev() free_netdev(ndev) // free priv ravb_tx_timeout_work() // use priv unregister_netdev() will call .ndo_stop() so that ravb_stop() is called. And, after phy_stop() is called, netif_carrier_off() is also called. So that .ndo_tx_timeout() will not be called after phy_stop().
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2024-07-24 20:38 UTC
Impacted products
Vendor Product Version CPE status
Linux Linux Affected: c156633f1353264634135dea86ffcae74f2122fc , < 65d34cfd4e347054eb4193bc95d9da7eaa72dee5 (git)
Affected: c156633f1353264634135dea86ffcae74f2122fc , < db9aafa19547833240f58c2998aed7baf414dc82 (git)
Affected: c156633f1353264634135dea86ffcae74f2122fc , < 616761cf9df9af838c0a1a1232a69322a9eb67e6 (git)
Affected: c156633f1353264634135dea86ffcae74f2122fc , < 6f6fa8061f756aedb93af12a8a5d3cf659127965 (git)
Affected: c156633f1353264634135dea86ffcae74f2122fc , < 105abd68ad8f781985113aee2e92e0702b133705 (git)
Affected: c156633f1353264634135dea86ffcae74f2122fc , < 3971442870713de527684398416970cf025b4f89 (git)
guessed Create a notification for this product.
Linux Linux Affected: 4.2
Unaffected: 0 , < 4.2 (semver)
Unaffected: 5.4.259 , ≤ 5.4.* (semver)
Unaffected: 5.10.199 , ≤ 5.10.* (semver)
Unaffected: 5.15.136 , ≤ 5.15.* (semver)
Unaffected: 6.1.59 , ≤ 6.1.* (semver)
Unaffected: 6.5.8 , ≤ 6.5.* (semver)
Unaffected: 6.6 , ≤ * (original_commit_for_fix)
guessed Create a notification for this product.
Show details on NVD website

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    "redhat_vex": {
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      "current_release_date": "2026-08-04T22:57:46+00:00",
      "cve": "CVE-2023-52509",
      "id": "CVE-2023-52509",
      "initial_release_date": "2023-01-01T00:00:00+00:00",
      "product_status:known_not_affected": "198",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "kernel: ravb: Fix use-after-free issue in ravb_tx_timeout_work()",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2023/cve-2023-52509.json",
      "version": "3"
    },
    "suse_vex": {
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      "current_release_date": "2026-09-02T01:49:16Z",
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      "initial_release_date": "2024-03-05T04:31:35Z",
      "product_status:known_not_affected": "216",
      "product_status:recommended": "768",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2023-52509",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2023-52509.json",
      "version": "60"
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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.
  • 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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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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