GSD-2023-46802
Vulnerability from gsd - Updated: 2023-12-13 01:20Details
e-Tax software Version3.0.10 and earlier improperly restricts XML external entity references (XXE) due to the configuration of the embedded XML parser. By processing a specially crafted XML file, arbitrary files on the system may be read by an attacker.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2023-46802",
"id": "GSD-2023-46802"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
"CVE-2023-46802"
],
"details": "e-Tax software Version3.0.10 and earlier improperly restricts XML external entity references (XXE) due to the configuration of the embedded XML parser. By processing a specially crafted XML file, arbitrary files on the system may be read by an attacker.",
"id": "GSD-2023-46802",
"modified": "2023-12-13T01:20:53.053911Z",
"schema_version": "1.4.0"
}
},
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"version_affected": "=",
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"vendor_name": "National Tax Agency"
}
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}
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"problemtype": {
"problemtype_data": [
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"description": [
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"value": "XML external entities (XXE)"
}
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"name": "https://www.e-tax.nta.go.jp/topics/topics_20231102.htm",
"refsource": "MISC",
"url": "https://www.e-tax.nta.go.jp/topics/topics_20231102.htm"
},
{
"name": "https://jvn.jp/en/jp/JVN14762986/",
"refsource": "MISC",
"url": "https://jvn.jp/en/jp/JVN14762986/"
}
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"versionEndIncluding": "3.0.10",
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"description": {
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}
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},
"problemtype": {
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"tags": [
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},
{
"name": "https://jvn.jp/en/jp/JVN14762986/",
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"tags": [
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},
"impact": {
"baseMetricV3": {
"cvssV3": {
"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "NONE",
"baseScore": 5.5,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "HIGH",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
"version": "3.1"
},
"exploitabilityScore": 1.8,
"impactScore": 3.6
}
},
"lastModifiedDate": "2023-11-14T15:30Z",
"publishedDate": "2023-11-06T02:15Z"
}
}
}
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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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