FKIE_CVE-2026-89632
Vulnerability from fkie_nvd - Published: 2026-09-11 20:19 - Updated: 2026-09-13 07:17
Severity
Summary
In the Linux kernel, the following vulnerability has been resolved:
smb: client: fix use-before-check of ReparseDataLength in reparse_buf_ptr()
reparse_buf_ptr() reads buf->ReparseDataLength before checking that
count covers the full fixed header:
buf = (struct reparse_data_buffer *)((u8 *)io + off);
len = sizeof(*buf); /* 8 bytes */
rdlen = le16_to_cpu(buf->ReparseDataLength); /* offset 4, 2 bytes */
if (count < len || count < rdlen + len) /* check comes after */
struct reparse_data_buffer has ReparseDataLength at offset 4. If a
server returns OutputCount < 6, the read at offset 4-5 reaches past
the end of the received data. The off+count bounds against iov_len
were already validated, but that does not protect against count being
smaller than sizeof(*buf).
Split the check: verify count >= sizeof(*buf) before reading
ReparseDataLength, then verify count covers the data region.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Linux",
"programFiles": [
"fs/smb/client/smb2inode.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"lessThan": "711cf71300d7992f450600df8864917d3538679f",
"status": "affected",
"version": "a158bb66b1373866d9fd5997565a58a573085539",
"versionType": "git"
},
{
"lessThan": "05f78e6cf34ea3a285053bd5999e08e8ac298bd5",
"status": "affected",
"version": "a158bb66b1373866d9fd5997565a58a573085539",
"versionType": "git"
}
]
},
{
"defaultStatus": "unaffected",
"product": "Linux",
"programFiles": [
"fs/smb/client/smb2inode.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"lessThan": "7.2.4",
"status": "affected",
"version": "6.6.32",
"versionType": "semver"
},
{
"lessThan": "7.3-rc1",
"status": "affected",
"version": "6.6.32",
"versionType": "semver"
}
]
}
],
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "In the Linux kernel, the following vulnerability has been resolved:\n\nsmb: client: fix use-before-check of ReparseDataLength in reparse_buf_ptr()\n\nreparse_buf_ptr() reads buf-\u003eReparseDataLength before checking that\ncount covers the full fixed header:\n\n buf = (struct reparse_data_buffer *)((u8 *)io + off);\n len = sizeof(*buf); /* 8 bytes */\n rdlen = le16_to_cpu(buf-\u003eReparseDataLength); /* offset 4, 2 bytes */\n\n if (count \u003c len || count \u003c rdlen + len) /* check comes after */\n\nstruct reparse_data_buffer has ReparseDataLength at offset 4. If a\nserver returns OutputCount \u003c 6, the read at offset 4-5 reaches past\nthe end of the received data. The off+count bounds against iov_len\nwere already validated, but that does not protect against count being\nsmaller than sizeof(*buf).\n\nSplit the check: verify count \u003e= sizeof(*buf) before reading\nReparseDataLength, then verify count covers the data region."
}
],
"id": "CVE-2026-89632",
"lastModified": "2026-09-13T07:17:28.300",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 8.2,
"baseSeverity": "HIGH",
"confidentialityImpact": "LOW",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 4.2,
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"type": "Secondary"
}
]
},
"published": "2026-09-11T20:19:48.763",
"references": [
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"url": "https://git.kernel.org/stable/c/05f78e6cf34ea3a285053bd5999e08e8ac298bd5"
},
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"url": "https://git.kernel.org/stable/c/711cf71300d7992f450600df8864917d3538679f"
}
],
"sourceIdentifier": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"vulnStatus": "Received"
}
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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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