FKIE_CVE-2022-44564
Vulnerability from fkie_nvd - Published: 2022-12-28 18:15 - Updated: 2026-06-17 05:08
Severity
7.8 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
7.8 (High) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
7.8 (High) - CVSS:3.1/
Summary
Huawei Aslan Children's Watch has a path traversal vulnerability. Successful exploitation may allow attackers to access or modify protected system resources.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| huawei | aslan-al10_firmware | * | |
| huawei | aslan-al10 | - |
{
"affected": [
{
"affectedData": [
{
"product": "Aslan-AL10",
"vendor": "Huawei",
"versions": [
{
"status": "affected",
"version": "11.1.0.118(C00M06)-11.1.0.10118(C00M06)"
}
]
}
],
"source": "psirt@huawei.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:o:huawei:aslan-al10_firmware:*:*:*:*:*:*:*:*",
"matchCriteriaId": "E6AB1275-19D9-4C37-9BBB-BAE86B4E4BDF",
"versionEndIncluding": "11.1.0.10118\\(c00m06\\)",
"versionStartIncluding": "11.1.0.118\\(c00m06\\)",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
},
{
"cpeMatch": [
{
"criteria": "cpe:2.3:h:huawei:aslan-al10:-:*:*:*:*:*:*:*",
"matchCriteriaId": "8A2ADEF3-E411-4AB7-B200-DAAD5750A58C",
"vulnerable": false
}
],
"negate": false,
"operator": "OR"
}
],
"operator": "AND"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Huawei Aslan Children\u0027s Watch has a path traversal vulnerability. Successful exploitation may allow attackers to access or modify protected system resources."
},
{
"lang": "es",
"value": "Huawei Aslan Children\u0027s Watch tiene una vulnerabilidad de path traversal. La explotaci\u00f3n exitosa puede permitir a los atacantes acceder o modificar recursos protegidos del sistema."
}
],
"id": "CVE-2022-44564",
"lastModified": "2026-06-17T05:08:31.677",
"metrics": {
"cvssMetricV31": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9,
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 7.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "LOW",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 5.9,
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
],
"ssvcV203": [
{
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"ssvcData": {
"id": "CVE-2022-44564",
"options": [
{
"exploitation": "none"
},
{
"automatable": "no"
},
{
"technicalImpact": "total"
}
],
"role": "CISA Coordinator",
"timestamp": "2025-04-11T16:09:56.967737Z",
"version": "2.0.3"
}
}
]
},
"published": "2022-12-28T18:15:09.090",
"references": [
{
"source": "psirt@huawei.com",
"tags": [
"Vendor Advisory"
],
"url": "https://www.huawei.com/en/psirt/security-advisories/huawei-sa-20221102-01-d002dd8e-en"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Vendor Advisory"
],
"url": "https://www.huawei.com/en/psirt/security-advisories/huawei-sa-20221102-01-d002dd8e-en"
}
],
"sourceIdentifier": "psirt@huawei.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-22"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
},
{
"description": [
{
"lang": "en",
"value": "CWE-22"
}
],
"source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
"type": "Secondary"
}
]
}
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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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