CVE-2026-43374 (GCVE-0-2026-43374)
Vulnerability from cvelistv5 – Published: 2026-05-08 14:21 – Updated: 2026-08-05 12:27
VLAI
EPSS
VEX
Title
net: nexthop: fix percpu use-after-free in remove_nh_grp_entry
Summary
In the Linux kernel, the following vulnerability has been resolved:
net: nexthop: fix percpu use-after-free in remove_nh_grp_entry
When removing a nexthop from a group, remove_nh_grp_entry() publishes
the new group via rcu_assign_pointer() then immediately frees the
removed entry's percpu stats with free_percpu(). However, the
synchronize_net() grace period in the caller remove_nexthop_from_groups()
runs after the free. RCU readers that entered before the publish still
see the old group and can dereference the freed stats via
nh_grp_entry_stats_inc() -> get_cpu_ptr(nhge->stats), causing a
use-after-free on percpu memory.
Fix by deferring the free_percpu() until after synchronize_net() in the
caller. Removed entries are chained via nh_list onto a local deferred
free list. After the grace period completes and all RCU readers have
finished, the percpu stats are safely freed.
Severity
7.8 (High)
Assigner
References
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Linux | Linux |
Affected:
f4676ea74b8549cd88dbfe2a592ce4530039e61f , < abf4feaee6405f1441929c6ebe7a250f2cd170a7
(git)
Affected: f4676ea74b8549cd88dbfe2a592ce4530039e61f , < ab5ebab9664214ba41a7633cb4e72f128204f924 (git) Affected: f4676ea74b8549cd88dbfe2a592ce4530039e61f , < 9e08ad731862b22a87cc55f752e16d66cdc9e231 (git) Affected: f4676ea74b8549cd88dbfe2a592ce4530039e61f , < b2662e7593e94ae09b1cf7ee5f09160a3612bcb2 (git) |
guessed | |
| Linux | Linux |
Affected:
6.9
Unaffected: 0 , < 6.9 (semver) Unaffected: 6.12.78 , ≤ 6.12.* (semver) Unaffected: 6.18.19 , ≤ 6.18.* (semver) Unaffected: 6.19.9 , ≤ 6.19.* (semver) Unaffected: 7.0 , ≤ * (original_commit_for_fix) |
guessed |
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"source": "Red Hat CSAF VEX",
"status": "final",
"title": "kernel: net: nexthop: fix percpu use-after-free in remove_nh_grp_entry",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-43374.json",
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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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