GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

GHSA-473C-M7P3-H25C

Vulnerability from github – Published: 2025-10-22 21:31 – Updated: 2025-10-22 21:31
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

be2net: Fix buffer overflow in be_get_module_eeprom

be_cmd_read_port_transceiver_data assumes that it is given a buffer that is at least PAGE_DATA_LEN long, or twice that if the module supports SFF 8472. However, this is not always the case.

Fix this by passing the desired offset and length to be_cmd_read_port_transceiver_data so that we only copy the bytes once.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-49581"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-02-26T07:01:33Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nbe2net: Fix buffer overflow in be_get_module_eeprom\n\nbe_cmd_read_port_transceiver_data assumes that it is given a buffer that\nis at least PAGE_DATA_LEN long, or twice that if the module supports SFF\n8472. However, this is not always the case.\n\nFix this by passing the desired offset and length to\nbe_cmd_read_port_transceiver_data so that we only copy the bytes once.",
  "id": "GHSA-473c-m7p3-h25c",
  "modified": "2025-10-22T21:31:16Z",
  "published": "2025-10-22T21:31:16Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-49581"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/18043da94c023f3ef09c15017bdb04e8f695ef10"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/665cbe91de2f7c97c51ca8fce39aae26477c1948"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8ff4f9df73e5c551a72ee6034886c17e8de6596d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/a5a8fc0679a8fd58d47aa2ebcfc5742631f753f9"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/a8569f76df7ec5b4b51155c57523a0b356db5741"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/aba8ff847f4f927ad7a1a1ee4a9f29989a1a728f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d7241f679a59cfe27f92cb5c6272cb429fb1f7ec"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/fe4473fc7940f14c4a12db873b9729134c212654"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…