GHSA-FW9R-626Q-5X54
Vulnerability from github – Published: 2026-09-17 18:32 – Updated: 2026-09-18 18:31
VLAI
Details
In the Linux kernel, the following vulnerability has been resolved:
drm/amdgpu/pm/powerplay: bounds-check voltage index in SMU7 lookup
vddInd and vddcInd fields from VBIOS-parsed tables are used to index into voltage lookup tables without a bounds check. Return -EINVAL when any index is out of range.
Severity
7.1 (High)
{
"affected": [],
"aliases": [
"CVE-2026-93178"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-09-17T17:18:13Z",
"severity": "HIGH"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\ndrm/amdgpu/pm/powerplay: bounds-check voltage index in SMU7 lookup\n\nvddInd and vddcInd fields from VBIOS-parsed tables are used to index into\nvoltage lookup tables without a bounds check. Return -EINVAL when any\nindex is out of range.",
"id": "GHSA-fw9r-626q-5x54",
"modified": "2026-09-18T18:31:34Z",
"published": "2026-09-17T18:32:13Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-93178"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/1664327ce797e09e387dc10cbbaa5b8d76558d2c"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/3a8a05477cda6c8293e2b629495b42981dcaba32"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/6f08c001fa6e8212930d694540ae8d9d6d3fb58a"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/745297208d31222f916cc04da313cb737b997935"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/8a3db9f593b643904c6cc6d8a3f211c84ca6cf8a"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/ce0d8e72836c9d3710a160ad848b0f1d096075e3"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/d9ef085114d1e3c2c1f869c0bdb275a7b358ce8b"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f925d317d84d401d642e537ea18ee12f67cb6983"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H",
"type": "CVSS_V3"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
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.
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.
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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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