GSD-2011-3923
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Apache Struts before 2.3.1.2 allows remote attackers to bypass security protections in the ParameterInterceptor class and execute arbitrary commands.
Aliases
Aliases
{
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"alias": "CVE-2011-3923",
"description": "Apache Struts before 2.3.1.2 allows remote attackers to bypass security protections in the ParameterInterceptor class and execute arbitrary commands.",
"id": "GSD-2011-3923",
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"https://packetstormsecurity.com/files/cve/CVE-2011-3923"
]
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"gsd": {
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"remediation": "unknown",
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"id": "GSD-2011-3923",
"modified": "2023-12-13T01:19:09.141269Z",
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"affected_range": "[2-alpha0,2.3.1.1]",
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"cvss_v2": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
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"cwe_ids": [
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"CWE-732",
"CWE-937"
],
"date": "2019-12-02",
"description": "OGNL provides, among other features, extensive expression evaluation capabilities. The vulnerability allows a malicious user to bypass all the protections (regex pattern, deny method invocation) built into the `ParametersInterceptor`, thus being able to inject a malicious expression in any exposed string variable for further evaluation.",
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"package_slug": "maven/org.apache.struts/struts2-core",
"pubdate": "2019-11-01",
"solution": "Upgrade to version 2.3.1.2 or above.",
"title": "Remote code execution via OGNL injention in HTTP parameter values",
"urls": [
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"impact": {
"baseMetricV2": {
"acInsufInfo": false,
"cvssV2": {
"accessComplexity": "LOW",
"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 7.5,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "PARTIAL",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
"version": "2.0"
},
"exploitabilityScore": 10.0,
"impactScore": 6.4,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "HIGH",
"userInteractionRequired": false
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"attackVector": "NETWORK",
"availabilityImpact": "HIGH",
"baseScore": 9.8,
"baseSeverity": "CRITICAL",
"confidentialityImpact": "HIGH",
"integrityImpact": "HIGH",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"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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},
"lastModifiedDate": "2019-12-02T18:39Z",
"publishedDate": "2019-11-01T14:15Z"
}
}
}
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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.
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- 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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