FKIE_CVE-2022-22274
Vulnerability from fkie_nvd - Published: 2022-03-25 23:15 - Updated: 2026-06-17 04:28
Severity
Summary
A Stack-based buffer overflow vulnerability in the SonicOS via HTTP request allows a remote unauthenticated attacker to cause Denial of Service (DoS) or potentially results in code execution in the firewall.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| sonicwall | sonicos | * | |
| sonicwall | nsa_2700 | - | |
| sonicwall | nsa_3700 | - | |
| sonicwall | nsa_4700 | - | |
| sonicwall | nsa_5700 | - | |
| sonicwall | nsa_6700 | - | |
| sonicwall | nssp_10700 | - | |
| sonicwall | nssp_11700 | - | |
| sonicwall | nssp_13700 | - | |
| sonicwall | nsv_270 | - | |
| sonicwall | nsv_470 | - | |
| sonicwall | nsv_870 | - | |
| sonicwall | tz270 | - | |
| sonicwall | tz270w | - | |
| sonicwall | tz370 | - | |
| sonicwall | tz370w | - | |
| sonicwall | tz470 | - | |
| sonicwall | tz470w | - | |
| sonicwall | tz570 | - | |
| sonicwall | tz570p | - | |
| sonicwall | tz570w | - | |
| sonicwall | tz670 | - | |
| sonicwall | sonicos | * | |
| sonicwall | nssp_15700 | - | |
| sonicwall | sonicosv | * | |
| sonicwall | nsv_10 | - | |
| sonicwall | nsv_100 | - | |
| sonicwall | nsv_1600 | - | |
| sonicwall | nsv_200 | - | |
| sonicwall | nsv_25 | - | |
| sonicwall | nsv_300 | - | |
| sonicwall | nsv_400 | - | |
| sonicwall | nsv_50 | - | |
| sonicwall | nsv_800 | - |
{
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{
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},
{
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},
{
"status": "affected",
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}
]
}
],
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}
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"cveTags": [],
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{
"lang": "en",
"value": "A Stack-based buffer overflow vulnerability in the SonicOS via HTTP request allows a remote unauthenticated attacker to cause Denial of Service (DoS) or potentially results in code execution in the firewall."
},
{
"lang": "es",
"value": "Una vulnerabilidad de desbordamiento de b\u00fafer en la regi\u00f3n Stack de la memoria en SonicOS por medio de una petici\u00f3n HTTP permite a un atacante remoto no autenticado causar una denegaci\u00f3n de servicio (DoS) o potencialmente resultando en una ejecuci\u00f3n de c\u00f3digo en el firewall"
}
],
"id": "CVE-2022-22274",
"lastModified": "2026-06-17T04:28:09.180",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
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"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 6.4,
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
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"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
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"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
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},
"published": "2022-03-25T23:15:08.353",
"references": [
{
"source": "PSIRT@sonicwall.com",
"tags": [
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"url": "https://psirt.global.sonicwall.com/vuln-detail/SNWLID-2022-0003"
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"weaknesses": [
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"value": "CWE-121"
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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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