GHSA-49WG-X228-H4JH
Vulnerability from github – Published: 2026-09-17 18:31 – Updated: 2026-09-17 18:31
VLAI
Details
In the Linux kernel, the following vulnerability has been resolved:
arm64: hibernate: Restore DAIF state on error
Sashiko AI has reported that if swsusp_mte_save_tags() for some reason fails we return from swsusp_arch_suspend() with DAIF being masked - that is not what we'd expect. Restore the saved DAIF state before returning from the error path.
{
"affected": [],
"aliases": [
"CVE-2026-90290"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-09-17T17:17:26Z",
"severity": null
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\narm64: hibernate: Restore DAIF state on error\n\nSashiko AI has reported that if swsusp_mte_save_tags() for some reason\nfails we return from swsusp_arch_suspend() with DAIF being masked -\nthat is not what we\u0027d expect. Restore the saved DAIF state before\nreturning from the error path.",
"id": "GHSA-49wg-x228-h4jh",
"modified": "2026-09-17T18:31:59Z",
"published": "2026-09-17T18:31:59Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-90290"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/2c941f383a53e188cd6fe3a129eb9b52b298e683"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/519e7de2c4c7b92ef57d4404b7e564aa9be24143"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/541549827889d0380fd73f8aacb5de6ef7a5a1ac"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/77053624d03359a4e2ec47d7106639ec9a498c2b"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/ad3839fe2114bb092846df79edd8d119e148b8c3"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/c8c6835f62a7f9fc68865e85397d13a2dc9210fb"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/cb51a05498e755d900900ff4b8503b4da4325996"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/f5693dfaf28d66e7e880feafd1778d3715869efc"
}
],
"schema_version": "1.4.0",
"severity": []
}
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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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