FKIE_CVE-2026-80960
Vulnerability from fkie_nvd - Published: 2026-09-11 20:19 - Updated: 2026-09-11 20:19
Severity
Summary
In the Linux kernel, the following vulnerability has been resolved:
dm-pcache: validate on-media seg_num against the cache device size
seg_num is read from the crc32c-only superblock, so whoever supplies the
cache device on a table load (CAP_SYS_ADMIN) controls it. It sizes
cache->segments[] and is the value every later on-media segment id is
bounded against, yet it is never checked against the device. Because
cache_dev->mapping is the direct map of the pmem, CACHE_DEV_SEGMENT() for
a segment id past the device resolves to ordinary kernel memory beyond
the mapping; a new-cache init reaching such an id has cache_seg_init() ->
cache_dev_zero_range() memset() 12 KiB over that memory -- an
out-of-bounds write into the kernel heap at table load. A zero seg_num
makes the segment allocations ZERO_SIZE_PTR.
Reject a seg_num that is zero, larger than the device can hold, or larger
than PCACHE_CACHE_SEGS_MAX before it is used.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"defaultStatus": "unaffected",
"product": "Linux",
"programFiles": [
"drivers/md/dm-pcache/cache_dev.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"lessThan": "91b93fe5cf4d62d5ecc642a6c8f15a3c11b00e3c",
"status": "affected",
"version": "1d57628ff95b32d5cfa8d8f50e07690c161e9cf0",
"versionType": "git"
},
{
"lessThan": "e889c0ee81165fc90aad2979b51f930f77895703",
"status": "affected",
"version": "1d57628ff95b32d5cfa8d8f50e07690c161e9cf0",
"versionType": "git"
},
{
"lessThan": "62d92e45abe9e087370f9fc5d876b95673aced34",
"status": "affected",
"version": "1d57628ff95b32d5cfa8d8f50e07690c161e9cf0",
"versionType": "git"
}
]
},
{
"defaultStatus": "affected",
"product": "Linux",
"programFiles": [
"drivers/md/dm-pcache/cache_dev.c"
],
"repo": "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git",
"vendor": "Linux",
"versions": [
{
"status": "affected",
"version": "6.18"
},
{
"lessThan": "6.18",
"status": "unaffected",
"version": "0",
"versionType": "semver"
},
{
"lessThanOrEqual": "6.18.*",
"status": "unaffected",
"version": "6.18.50",
"versionType": "semver"
},
{
"lessThanOrEqual": "7.2.*",
"status": "unaffected",
"version": "7.2.4",
"versionType": "semver"
},
{
"lessThanOrEqual": "*",
"status": "unaffected",
"version": "7.3-rc1",
"versionType": "original_commit_for_fix"
}
]
}
],
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "In the Linux kernel, the following vulnerability has been resolved:\n\ndm-pcache: validate on-media seg_num against the cache device size\n\nseg_num is read from the crc32c-only superblock, so whoever supplies the\ncache device on a table load (CAP_SYS_ADMIN) controls it. It sizes\ncache-\u003esegments[] and is the value every later on-media segment id is\nbounded against, yet it is never checked against the device. Because\ncache_dev-\u003emapping is the direct map of the pmem, CACHE_DEV_SEGMENT() for\na segment id past the device resolves to ordinary kernel memory beyond\nthe mapping; a new-cache init reaching such an id has cache_seg_init() -\u003e\ncache_dev_zero_range() memset() 12 KiB over that memory -- an\nout-of-bounds write into the kernel heap at table load. A zero seg_num\nmakes the segment allocations ZERO_SIZE_PTR.\n\nReject a seg_num that is zero, larger than the device can hold, or larger\nthan PCACHE_CACHE_SEGS_MAX before it is used."
}
],
"id": "CVE-2026-80960",
"lastModified": "2026-09-11T20:19:01.863",
"metrics": {},
"published": "2026-09-11T20:19:01.863",
"references": [
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"url": "https://git.kernel.org/stable/c/62d92e45abe9e087370f9fc5d876b95673aced34"
},
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"url": "https://git.kernel.org/stable/c/91b93fe5cf4d62d5ecc642a6c8f15a3c11b00e3c"
},
{
"source": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"url": "https://git.kernel.org/stable/c/e889c0ee81165fc90aad2979b51f930f77895703"
}
],
"sourceIdentifier": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"vulnStatus": "Received"
}
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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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