GHSA-9MRQ-M3FM-3H9W
Vulnerability from github – Published: 2026-08-28 09:31 – Updated: 2026-08-29 09:30In the Linux kernel, the following vulnerability has been resolved:
HID: core: Fix OOB read in hid_get_report for numbered reports
When a caller passes a size of 0 to hid_report_raw_event() for a numbered report, the function originally called hid_get_report() before performing any size validation.
Inside hid_get_report(), if the report is numbered (report_enum->numbered is true), it unconditionally dereferences data[0] to extract the report ID. With a size of 0, this results in an out-of-bounds read or kernel panic.
Fix this by moving the numbered report size validation check before the call to hid_get_report(), ensuring that size is at least 1 before dereferencing the data pointer.
{
"affected": [],
"aliases": [
"CVE-2026-80604"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-08-28T08:16:44Z",
"severity": "HIGH"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\nHID: core: Fix OOB read in hid_get_report for numbered reports\n\nWhen a caller passes a size of 0 to hid_report_raw_event() for a\nnumbered report, the function originally called hid_get_report() before\nperforming any size validation.\n\nInside hid_get_report(), if the report is numbered (report_enum-\u003enumbered\nis true), it unconditionally dereferences data[0] to extract the report ID.\nWith a size of 0, this results in an out-of-bounds read or kernel panic.\n\nFix this by moving the numbered report size validation check before the\ncall to hid_get_report(), ensuring that size is at least 1 before\ndereferencing the data pointer.",
"id": "GHSA-9mrq-m3fm-3h9w",
"modified": "2026-08-29T09:30:25Z",
"published": "2026-08-28T09:31:46Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-80604"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/30ff978af92cb51c9ba99f96fc4f4ac80d7001ba"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/af1a9b65ebe8a948eda805c14b78d4d0767cb1b5"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/c1fc0d3aff26ec9ff885b3e4c92eba98cf349678"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/c39f5765ad840b71ff8db812d0210f216cca96e4"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/c973d53bcd420b58c4a34c68198746286d77e9fa"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/dd395744e4ed87956fcbf81ecc6a20c51e35fa4e"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f7e8117e42b20c30d2a5edab82c944a5e381d791"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f8896b684e246f3f00f45ba2b6803ae59b9cc768"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
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.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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.