GHSA-8J5C-4J8R-8M5M
Vulnerability from github – Published: 2026-10-18 18:32 – Updated: 2026-10-18 18:32In the Linux kernel, the following vulnerability has been resolved:
KVM: SEV: Do cache maintenance on the source VM before clearing SEV state
Explicitly flush caches after intra-host migration before clearing "SEV active" on the source VM, as doing cache maintenance afterwards creates a tiny window where memory reclaim could return memory to the host without performing a cache flush, e.g. as pointed out by Sashiko:
CPU1 in sev_migrate_from(): src->active = false;
CPU2 running concurrent unmap: Since active is false, the automatic cache flush in sev_guest_memory_reclaimed is skipped. The host frees and reallocates the page.
CPU1 in sev_migrate_from(): sev_writeback_caches(src_kvm); Executes a hardware cache flush (wbnoinvd), which writes the guest's old dirty ciphertext over the new page owner's data.
{
"affected": [],
"aliases": [
"CVE-2026-98718"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-10-18T16:17:25Z",
"severity": null
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\nKVM: SEV: Do cache maintenance on the source VM *before* clearing SEV state\n\nExplicitly flush caches after intra-host migration before clearing \"SEV\nactive\" on the source VM, as doing cache maintenance afterwards creates a\ntiny window where memory reclaim could return memory to the host without\nperforming a cache flush, e.g. as pointed out by Sashiko:\n\n CPU1 in sev_migrate_from():\n src-\u003eactive = false;\n\n CPU2 running concurrent unmap:\n Since active is false, the automatic cache flush in\n sev_guest_memory_reclaimed is skipped.\n The host frees and reallocates the page.\n\n CPU1 in sev_migrate_from():\n sev_writeback_caches(src_kvm);\n Executes a hardware cache flush (wbnoinvd), which writes the guest\u0027s old\n dirty ciphertext over the new page owner\u0027s data.",
"id": "GHSA-8j5c-4j8r-8m5m",
"modified": "2026-10-18T18:32:00Z",
"published": "2026-10-18T18:32:00Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-98718"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/8b7d4f68fef96cebe0b6dbb6e5607772337f7369"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/973ea70393e885e540f714904e51bc6cac80e3d7"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/de83ff6a4d8f3618473bedb3c4400020c22e8a8a"
}
],
"schema_version": "1.4.0",
"severity": []
}
Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
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.