GHSA-66G6-R4V9-4XGM
Vulnerability from github – Published: 2026-10-23 15:31 – Updated: 2026-10-23 15:31In the Linux kernel, the following vulnerability has been resolved:
ipv4: do not warn on route notification size race
Commit 680aea08e78c ("net: ipv4: Emit notification when fib hardware flags are changed") added asynchronous route notifications for hardware flag changes.
fib_alias_hw_flags_set() sizes the skb with fib_nlmsg_size() and later fills it with fib_dump_info() while holding only RCU. With nexthop compatibility mode enabled, a concurrent replacement can grow the group between these independent snapshots. fib_dump_info() can then legitimately return -EMSGSIZE, so the warning does not prove a sizing bug.
Remove the warning. The existing error path still frees the skb and reports the error to listeners.
{
"affected": [],
"aliases": [
"CVE-2026-99071"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2026-10-23T13:17:31Z",
"severity": null
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\nipv4: do not warn on route notification size race\n\nCommit 680aea08e78c (\"net: ipv4: Emit notification when fib hardware\nflags are changed\") added asynchronous route notifications for hardware\nflag changes.\n\nfib_alias_hw_flags_set() sizes the skb with fib_nlmsg_size() and later\nfills it with fib_dump_info() while holding only RCU. With nexthop\ncompatibility mode enabled, a concurrent replacement can grow the group\nbetween these independent snapshots. fib_dump_info() can then\nlegitimately return -EMSGSIZE, so the warning does not prove a sizing bug.\n\nRemove the warning. The existing error path still frees the skb and\nreports the error to listeners.",
"id": "GHSA-66g6-r4v9-4xgm",
"modified": "2026-10-23T15:31:37Z",
"published": "2026-10-23T15:31:37Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-99071"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/088ba80eef85fa7a5ad8f9e7c82b403c99242b56"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/221ef5e1e44a044790f0f54e6aa237883f475a4d"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/78a1cf5c54b2f795c81fedb530755a8d01cc84f0"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/7dfa7ca97f3ac46353edd4cc44f7733758e4535b"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/e02a5b6588161673ef75a4bc5cdfb62bd493374d"
}
],
"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.