GSD-2019-10088
Vulnerability from gsd - Updated: 2023-12-13 01:23Details
A carefully crafted or corrupt zip file can cause an OOM in Apache Tika's RecursiveParserWrapper in versions 1.7-1.21. Users should upgrade to 1.22 or later.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2019-10088",
"description": "A carefully crafted or corrupt zip file can cause an OOM in Apache Tika\u0027s RecursiveParserWrapper in versions 1.7-1.21. Users should upgrade to 1.22 or later.",
"id": "GSD-2019-10088",
"references": [
"https://www.suse.com/security/cve/CVE-2019-10088.html"
]
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"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
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"modified": "2023-12-13T01:23:59.963648Z",
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{
"affected_range": "[1.7,1.21]",
"affected_versions": "All versions starting from 1.7 up to 1.21",
"credit": "RunningSnail",
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"cwe_ids": [
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"CWE-770",
"CWE-937"
],
"date": "2019-08-12",
"description": "A carefully crafted or corrupt zip file can cause an OOM in Apache Tika\u0027s `RecursiveParserWrapper`.",
"fixed_versions": [
"1.22"
],
"identifier": "CVE-2019-10088",
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"not_impacted": "All versions before 1.7, all versions after 1.21",
"package_slug": "maven/org.apache.tika/tika-core",
"pubdate": "2019-08-02",
"solution": "Upgrade to version 1.22 or above.",
"title": "Out of memory",
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"impact": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 6.8,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:M/Au:N/C:P/I:P/A:P",
"version": "2.0"
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"exploitabilityScore": 8.6,
"impactScore": 6.4,
"obtainAllPrivilege": false,
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"severity": "MEDIUM",
"userInteractionRequired": true
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"attackVector": "NETWORK",
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"baseScore": 8.8,
"baseSeverity": "HIGH",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "REQUIRED",
"vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
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},
"lastModifiedDate": "2020-08-24T17:37Z",
"publishedDate": "2019-08-02T19:15Z"
}
}
}
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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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