CVE-2023-53519 (GCVE-0-2023-53519)
Vulnerability from cvelistv5 – Published: 2025-10-01 11:46 – Updated: 2026-05-11 19:46
VLAI
EPSS
VEX
Title
media: v4l2-mem2mem: add lock to protect parameter num_rdy
Summary
In the Linux kernel, the following vulnerability has been resolved:
media: v4l2-mem2mem: add lock to protect parameter num_rdy
Getting below error when using KCSAN to check the driver. Adding lock to
protect parameter num_rdy when getting the value with function:
v4l2_m2m_num_src_bufs_ready/v4l2_m2m_num_dst_bufs_ready.
kworker/u16:3: [name:report&]BUG: KCSAN: data-race in v4l2_m2m_buf_queue
kworker/u16:3: [name:report&]
kworker/u16:3: [name:report&]read-write to 0xffffff8105f35b94 of 1 bytes by task 20865 on cpu 7:
kworker/u16:3: v4l2_m2m_buf_queue+0xd8/0x10c
Severity
5.5 (Medium)
Assigner
References
8 references
Impacted products
2 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Linux | Linux |
Affected:
908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < 690dd4780b3f4d755e4e7883e8c3d1b5052f6bf2
(git)
Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < 7fc7f87725805197388ba749a1801df33000fa50 (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < ef009fe2010ea2a3a7045ecb72729cf366e0967b (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < e52de26cb37459b16213438a2c82feb155dd3bbd (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < 1676748aa29099fc0abd71e0fb092e76e835f25c (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < c71aa5f1cf961264690f2560503ea396b6e3c680 (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < e01ea1c4191ee08440b5f86db98dff695e9cedf9 (git) Affected: 908a0d7c588ef87e5cf0a26805e6002a78ac9d13 , < 56b5c3e67b0f9af3f45cf393be048ee8d8a92694 (git) |
guessed | |
| Linux | Linux |
Affected:
2.6.39
Unaffected: 0 , < 2.6.39 (semver) Unaffected: 4.14.324 , ≤ 4.14.* (semver) Unaffected: 4.19.293 , ≤ 4.19.* (semver) Unaffected: 5.4.255 , ≤ 5.4.* (semver) Unaffected: 5.10.192 , ≤ 5.10.* (semver) Unaffected: 5.15.128 , ≤ 5.15.* (semver) Unaffected: 6.1.47 , ≤ 6.1.* (semver) Unaffected: 6.4.12 , ≤ 6.4.* (semver) Unaffected: 6.5 , ≤ * (original_commit_for_fix) |
guessed |
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},
{
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},
{
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},
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},
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}
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{
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},
{
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"datePublished": "2025-10-01T11:46:06.419Z",
"dateReserved": "2025-10-01T11:39:39.407Z",
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{
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"value": "In the Linux kernel, the following vulnerability has been resolved:\n\nmedia: v4l2-mem2mem: add lock to protect parameter num_rdy\n\nGetting below error when using KCSAN to check the driver. Adding lock to\nprotect parameter num_rdy when getting the value with function:\nv4l2_m2m_num_src_bufs_ready/v4l2_m2m_num_dst_bufs_ready.\n\nkworker/u16:3: [name:report\u0026]BUG: KCSAN: data-race in v4l2_m2m_buf_queue\nkworker/u16:3: [name:report\u0026]\n\nkworker/u16:3: [name:report\u0026]read-write to 0xffffff8105f35b94 of 1 bytes by task 20865 on cpu 7:\nkworker/u16:3:\u00a0 v4l2_m2m_buf_queue+0xd8/0x10c"
}
],
"id": "CVE-2023-53519",
"lastModified": "2026-06-17T06:45:31.193",
"metrics": {
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{
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 5.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
"version": "3.1"
},
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]
},
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{
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{
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{
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{
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],
"sourceIdentifier": "416baaa9-dc9f-4396-8d5f-8c081fb06d67",
"vulnStatus": "Analyzed",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-667"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
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}
},
"redhat_vex": {
"aggregate_severity": "Moderate",
"current_release_date": "2026-06-29T22:27:23+00:00",
"cve": "CVE-2023-53519",
"id": "CVE-2023-53519",
"initial_release_date": "2023-01-01T00:00:00+00:00",
"product_status:fixed": "305",
"product_status:known_affected": "22",
"product_status:known_not_affected": "166",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "kernel: media: v4l2-mem2mem: add lock to protect parameter num_rdy",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2023/cve-2023-53519.json",
"version": "3"
}
}
}
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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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