FKIE_CVE-2013-5654
Vulnerability from fkie_nvd - Published: 2019-02-15 21:29 - Updated: 2026-06-16 23:59
Severity
Summary
Vulnerability in YingZhi Python Programming Language v1.9 allows arbitrary anonymous uploads to the phone's storage
References
| URL | Tags | ||
|---|---|---|---|
| larry0@me.com | http://www.iphoneappstorm.com/iphone-apps/utilities/com.yingzhi.python/yingzhipython.php?id=493505744 | Product | |
| larry0@me.com | http://www.vapidlabs.com/advisory.php?v=94 | Exploit, Product, Third Party Advisory | |
| af854a3a-2127-422b-91ae-364da2661108 | http://www.iphoneappstorm.com/iphone-apps/utilities/com.yingzhi.python/yingzhipython.php?id=493505744 | Product | |
| af854a3a-2127-422b-91ae-364da2661108 | http://www.vapidlabs.com/advisory.php?v=94 | Exploit, Product, Third Party Advisory |
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| yingzhipython_project | yingzhipython | 1.9 |
{
"affected": [
{
"affectedData": [
{
"product": "YingZhi Python Programming Language",
"vendor": "YingZhi",
"versions": [
{
"lessThanOrEqual": "1.9",
"status": "affected",
"version": "unspecified",
"versionType": "custom"
}
]
}
],
"source": "larry0@me.com"
}
],
"configurations": [
{
"nodes": [
{
"cpeMatch": [
{
"criteria": "cpe:2.3:a:yingzhipython_project:yingzhipython:1.9:*:*:*:*:*:*:*",
"matchCriteriaId": "F6D003CF-A530-43A4-AAB2-4DB7AF7AE585",
"vulnerable": true
}
],
"negate": false,
"operator": "OR"
}
]
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "Vulnerability in YingZhi Python Programming Language v1.9 allows arbitrary anonymous uploads to the phone\u0027s storage"
},
{
"lang": "es",
"value": "Vulnerabilidad en YingZhi Python Programming Language v1.9 permite las subidas arbitrarias an\u00f3nimas en el almacenamiento del tel\u00e9fono."
}
],
"id": "CVE-2013-5654",
"lastModified": "2026-06-16T23:59:11.900",
"metrics": {
"cvssMetricV2": [
{
"acInsufInfo": false,
"baseSeverity": "HIGH",
"cvssData": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 9.4,
"confidentialityImpact": "COMPLETE",
"integrityImpact": "COMPLETE",
"vectorString": "AV:N/AC:L/Au:N/C:C/I:C/A:N",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 9.2,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"source": "nvd@nist.gov",
"type": "Primary",
"userInteractionRequired": false
}
],
"cvssMetricV30": [
{
"cvssData": {
"attackComplexity": "LOW",
"attackVector": "NETWORK",
"availabilityImpact": "NONE",
"baseScore": 9.1,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
"version": "3.0"
},
"exploitabilityScore": 3.9,
"impactScore": 5.2,
"source": "nvd@nist.gov",
"type": "Primary"
}
]
},
"published": "2019-02-15T21:29:00.347",
"references": [
{
"source": "larry0@me.com",
"tags": [
"Product"
],
"url": "http://www.iphoneappstorm.com/iphone-apps/utilities/com.yingzhi.python/yingzhipython.php?id=493505744"
},
{
"source": "larry0@me.com",
"tags": [
"Exploit",
"Product",
"Third Party Advisory"
],
"url": "http://www.vapidlabs.com/advisory.php?v=94"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Product"
],
"url": "http://www.iphoneappstorm.com/iphone-apps/utilities/com.yingzhi.python/yingzhipython.php?id=493505744"
},
{
"source": "af854a3a-2127-422b-91ae-364da2661108",
"tags": [
"Exploit",
"Product",
"Third Party Advisory"
],
"url": "http://www.vapidlabs.com/advisory.php?v=94"
}
],
"sourceIdentifier": "larry0@me.com",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-284"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
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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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