FKIE_CVE-2026-64037
Vulnerability from fkie_nvd - Published: 2026-07-19 16:17 - Updated: 2026-10-19 21:17
Severity
Summary
In the Linux kernel, the following vulnerability has been resolved:
wifi: iwlwifi: mld: fix TSO segmentation explosion when AMSDU is disabled
When the TLC notification disables AMSDU for a TID, the MLD driver sets
max_tid_amsdu_len to the sentinel value 1. The TSO segmentation path in
iwl_mld_tx_tso_segment() checks for zero but not for this sentinel,
allowing it to reach the num_subframes calculation:
num_subframes = (max_tid_amsdu_len + pad) / (subf_len + pad)
= (1 + 2) / (1534 + 2) = 0
This zero propagates to iwl_tx_tso_segment() which sets:
gso_size = num_subframes * mss = 0
Calling skb_gso_segment() with gso_size=0 creates over 32000 tiny
segments from a single GSO skb. This floods the TX ring with ~1024
micro-frames (the rest are purged), creating a massive burst of TX
completion events that can lead to memory corruption and a subsequent
use-after-free in TCP's retransmit queue (refcount underflow in
tcp_shifted_skb, NULL deref in tcp_rack_detect_loss).
The MVM driver is immune because it checks mvmsta->amsdu_enabled before
reaching the num_subframes calculation. The MLD driver has no equivalent
bitmap check and relies solely on max_tid_amsdu_len, which does not
catch the sentinel value.
Fix this by detecting the sentinel value (max_tid_amsdu_len == 1) at the
existing check and falling back to non-AMSDU TSO segmentation. Also add
a WARN_ON_ONCE guard after the num_subframes division as defense-in-depth
to catch any future code paths that produce zero through a different
mechanism.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| linux | linux_kernel | * | |
| linux | linux_kernel | * | |
| linux | linux_kernel | 7.1 | |
| linux | linux_kernel | 7.1 | |
| linux | linux_kernel | 7.1 | |
| linux | linux_kernel | 7.1 |
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Linux",
"programFiles": [
"drivers/net/wireless/intel/iwlwifi/mld/tx.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"lessThan": "9e360e610a73f62432e986775023d5382773f045",
"status": "affected",
"version": "d1e879ec600f9b3bdd253167533959facfefb17b",
"versionType": "git"
},
{
"lessThan": "cbe1c8245e4469d1aa6e12e5d913611376d23788",
"status": "affected",
"version": "d1e879ec600f9b3bdd253167533959facfefb17b",
"versionType": "git"
},
{
"lessThan": "92cee08dc4f00e77fd1317e4343c5d458b0abab7",
"status": "affected",
"version": "d1e879ec600f9b3bdd253167533959facfefb17b",
"versionType": "git"
}
]
},
{
"defaultStatus": "affected",
"product": "Linux",
"programFiles": [
"drivers/net/wireless/intel/iwlwifi/mld/tx.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"status": "affected",
"version": "6.15"
},
{
"lessThan": "6.15",
"status": "unaffected",
"version": "0",
"versionType": "semver"
},
{
"lessThanOrEqual": "6.18.*",
"status": "unaffected",
"version": "6.18.34",
"versionType": "semver"
},
{
"lessThanOrEqual": "7.0.*",
"status": "unaffected",
"version": "7.0.11",
"versionType": "semver"
},
{
"lessThanOrEqual": "*",
"status": "unaffected",
"version": "7.1",
"versionType": "original_commit_for_fix"
}
]
}
],
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:o:linux:linux_kernel:*:*:*:*:*:*:*:*",
"matchCriteriaId": "89E9B97C-FD82-4D2E-8426-3A1A703B2ED7",
"versionEndExcluding": "6.18.34",
"versionStartIncluding": "6.15",
"vulnerable": true
},
{
"criteria": "cpe:2.3:o:linux:linux_kernel:*:*:*:*:*:*:*:*",
"matchCriteriaId": "0520D091-FC52-4A50-AF07-70AE7D08B750",
"versionEndExcluding": "7.0.11",
"versionStartIncluding": "6.19",
"vulnerable": true
},
{
"criteria": "cpe:2.3:o:linux:linux_kernel:7.1:rc1:*:*:*:*:*:*",
"matchCriteriaId": "B1EF7059-E670-45F4-B422-54C40FA86390",
"vulnerable": true
},
{
"criteria": "cpe:2.3:o:linux:linux_kernel:7.1:rc2:*:*:*:*:*:*",
"matchCriteriaId": "0D38F0BF-A728-4133-A358-D44A2F7EE6D6",
"vulnerable": true
},
{
"criteria": "cpe:2.3:o:linux:linux_kernel:7.1:rc3:*:*:*:*:*:*",
"matchCriteriaId": "EC732D08-5F7B-46D9-B154-E60C7F4F0A97",
"vulnerable": true
},
{
"criteria": "cpe:2.3:o:linux:linux_kernel:7.1:rc4:*:*:*:*:*:*",
"matchCriteriaId": "E5910A9D-F60A-409A-B486-FE66BFEBA9B9",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "In the Linux kernel, the following vulnerability has been resolved:\n\nwifi: iwlwifi: mld: fix TSO segmentation explosion when AMSDU is disabled\n\nWhen the TLC notification disables AMSDU for a TID, the MLD driver sets\nmax_tid_amsdu_len to the sentinel value 1. The TSO segmentation path in\niwl_mld_tx_tso_segment() checks for zero but not for this sentinel,\nallowing it to reach the num_subframes calculation:\n\n num_subframes = (max_tid_amsdu_len + pad) / (subf_len + pad)\n = (1 + 2) / (1534 + 2) = 0\n\nThis zero propagates to iwl_tx_tso_segment() which sets:\n\n gso_size = num_subframes * mss = 0\n\nCalling skb_gso_segment() with gso_size=0 creates over 32000 tiny\nsegments from a single GSO skb. This floods the TX ring with ~1024\nmicro-frames (the rest are purged), creating a massive burst of TX\ncompletion events that can lead to memory corruption and a subsequent\nuse-after-free in TCP\u0027s retransmit queue (refcount underflow in\ntcp_shifted_skb, NULL deref in tcp_rack_detect_loss).\n\nThe MVM driver is immune because it checks mvmsta-\u003eamsdu_enabled before\nreaching the num_subframes calculation. The MLD driver has no equivalent\nbitmap check and relies solely on max_tid_amsdu_len, which does not\ncatch the sentinel value.\n\nFix this by detecting the sentinel value (max_tid_amsdu_len == 1) at the\nexisting check and falling back to non-AMSDU TSO segmentation. Also add\na WARN_ON_ONCE guard after the num_subframes division as defense-in-depth\nto catch any future code paths that produce zero through a different\nmechanism."
}
],
"id": "CVE-2026-64037",
"lastModified": "2026-10-19T21:17:21.430",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 5.9,
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2026-64037",
"options": [
{
"exploitation": "none"
},
{
"automatable": "yes"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2026-10-16T15:35:49.759974Z",
"version": "2.0.3"
}
}
]
},
"published": "2026-07-19T16:17:43.947",
"references": [
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"tags": [
"Patch"
],
"url": "https://git.kernel.org/stable/c/92cee08dc4f00e77fd1317e4343c5d458b0abab7"
},
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"tags": [
"Patch"
],
"url": "https://git.kernel.org/stable/c/9e360e610a73f62432e986775023d5382773f045"
},
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"tags": [
"Patch"
],
"url": "https://git.kernel.org/stable/c/cbe1c8245e4469d1aa6e12e5d913611376d23788"
}
],
"sourceIdentifier": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "NVD-CWE-noinfo"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-20"
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
]
}
Loading…
Loading…
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.
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.
Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
Loading timeline…
Loading…
Loading…
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.
Loading…
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.