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CVE-2022-49659 (GCVE-0-2022-49659)

Vulnerability from cvelistv5 – Published: 2025-02-26 02:23 – Updated: 2026-05-11 19:04
VLAI
Title
can: m_can: m_can_{read_fifo,echo_tx_event}(): shift timestamp to full 32 bits
Summary
In the Linux kernel, the following vulnerability has been resolved: can: m_can: m_can_{read_fifo,echo_tx_event}(): shift timestamp to full 32 bits In commit 1be37d3b0414 ("can: m_can: fix periph RX path: use rx-offload to ensure skbs are sent from softirq context") the RX path for peripheral devices was switched to RX-offload. Received CAN frames are pushed to RX-offload together with a timestamp. RX-offload is designed to handle overflows of the timestamp correctly, if 32 bit timestamps are provided. The timestamps of m_can core are only 16 bits wide. So this patch shifts them to full 32 bit before passing them to RX-offload.
Severity
5.5 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Assigner
References
Impacted products
Vendor Product Version CPE status
Linux Linux Affected: 1be37d3b0414e3db47f6fcba6c16286bbae0cb65 , < c7333f79888497bfd75dcd02a94eaf836dd1042c (git)
Affected: 1be37d3b0414e3db47f6fcba6c16286bbae0cb65 , < 2a2914a5bd7f38efe55a8372178146de82e0bce9 (git)
Affected: 1be37d3b0414e3db47f6fcba6c16286bbae0cb65 , < 4c3333693f07313f5f0145a922f14a7d3c0f4f21 (git)
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Linux Linux Affected: 5.13
Unaffected: 0 , < 5.13 (semver)
Unaffected: 5.15.54 , ≤ 5.15.* (semver)
Unaffected: 5.18.11 , ≤ 5.18.* (semver)
Unaffected: 5.19 , ≤ * (original_commit_for_fix)
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          "programFiles": [
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So this patch\\nshifts them to full 32 bit before passing them to RX-offload.\"},{\"lang\":\"es\",\"value\":\"En el kernel de Linux, se ha resuelto la siguiente vulnerabilidad: can: m_can: m_can_{read_fifo,echo_tx_event}(): cambiar la marca de tiempo a 32 bits completos En el commit 1be37d3b0414 (\\\"can: m_can: corregir la ruta RX de los perif\u00e9ricos: usar rx-offload para garantizar que los skbs se env\u00eden desde el contexto de softirq\\\"), la ruta RX para los dispositivos perif\u00e9ricos se cambi\u00f3 a RX-offload. Los marcos CAN recibidos se env\u00edan a RX-offload junto con una marca de tiempo. RX-offload est\u00e1 dise\u00f1ado para gestionar desbordamientos de la marca de tiempo correctamente, si se proporcionan marcas de tiempo de 32 bits. Las marcas de tiempo del n\u00facleo m_can tienen solo 16 bits de ancho. 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    "redhat_vex": {
      "aggregate_severity": "Moderate",
      "current_release_date": "2026-06-29T21:14:34+00:00",
      "cve": "CVE-2022-49659",
      "id": "CVE-2022-49659",
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      "product_status:fixed": "201",
      "product_status:known_affected": "22",
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      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "kernel: can: m_can: m_can_{read_fifo,echo_tx_event}(): shift timestamp to full 32 bits",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2022/cve-2022-49659.json",
      "version": "3"
    }
  }
}



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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

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.


Detection rules are retrieved from Rulezet.


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.