FKIE_CVE-2016-2549
Vulnerability from fkie_nvd - Published: 2016-04-27 17:59 - Updated: 2026-06-17 00:44
Severity
Summary
sound/core/hrtimer.c in the Linux kernel before 4.4.1 does not prevent recursive callback access, which allows local users to cause a denial of service (deadlock) via a crafted ioctl call.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| linux | linux_kernel | * |
{
"affected": [
{
"affectedData": [
{
"product": "n/a",
"vendor": "n/a",
"versions": [
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"status": "affected",
"version": "n/a"
}
]
}
],
"source": "cve@mitre.org"
}
],
"configurations": [
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"versionEndIncluding": "4.4",
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"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "sound/core/hrtimer.c in the Linux kernel before 4.4.1 does not prevent recursive callback access, which allows local users to cause a denial of service (deadlock) via a crafted ioctl call."
},
{
"lang": "es",
"value": "sound/core/hrtimer.c en el kernel de Linux en versiones anteriores a 4.4.1 no previene el acceso a la devoluci\u00f3n de llamadas recursivas, lo que permite a usuarios locales causar una denegaci\u00f3n de servicio (punto muerto) a trav\u00e9s de una llamada ioctl manipulada."
}
],
"id": "CVE-2016-2549",
"lastModified": "2026-06-17T00:44:16.680",
"metrics": {
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"acInsufInfo": false,
"baseSeverity": "LOW",
"cvssData": {
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"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 2.1,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
"version": "2.0"
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"published": "2016-04-27T17:59:18.990",
"references": [
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"url": "https://bugzilla.redhat.com/show_bug.cgi?id=1311570"
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"url": "https://github.com/torvalds/linux/commit/2ba1fe7a06d3624f9a7586d672b55f08f7c670f3"
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{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"url": "http://www.debian.org/security/2016/dsa-3503"
},
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"url": "http://www.ubuntu.com/usn/USN-2932-1"
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"sourceIdentifier": "cve@mitre.org",
"vulnStatus": "Modified",
"weaknesses": [
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"value": "CWE-20"
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"source": "nvd@nist.gov",
"type": "Primary"
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]
}
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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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