GSD-2017-2330
Vulnerability from gsd - Updated: 2023-12-13 01:21Details
A denial of service vulnerability in Juniper Networks NorthStar Controller Application prior to version 2.1.0 Service Pack 1 may allow an unauthenticated, local user, to create a fork bomb scenario, also known as a rabbit virus, or wabbit, which will create processes that replicate themselves, until all resources are consumed on the system, leading to a denial of service to the entire system until it is restarted. Continued attacks by an unauthenticated, local user, can lead to persistent denials of services.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2017-2330",
"description": "A denial of service vulnerability in Juniper Networks NorthStar Controller Application prior to version 2.1.0 Service Pack 1 may allow an unauthenticated, local user, to create a fork bomb scenario, also known as a rabbit virus, or wabbit, which will create processes that replicate themselves, until all resources are consumed on the system, leading to a denial of service to the entire system until it is restarted. Continued attacks by an unauthenticated, local user, can lead to persistent denials of services.",
"id": "GSD-2017-2330"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
"osvSchema": {
"aliases": [
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],
"details": "A denial of service vulnerability in Juniper Networks NorthStar Controller Application prior to version 2.1.0 Service Pack 1 may allow an unauthenticated, local user, to create a fork bomb scenario, also known as a rabbit virus, or wabbit, which will create processes that replicate themselves, until all resources are consumed on the system, leading to a denial of service to the entire system until it is restarted. Continued attacks by an unauthenticated, local user, can lead to persistent denials of services.",
"id": "GSD-2017-2330",
"modified": "2023-12-13T01:21:05.449197Z",
"schema_version": "1.4.0"
}
},
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"STATE": "PUBLIC"
},
"affects": {
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{
"product": {
"product_data": [
{
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"version": {
"version_data": [
{
"version_value": "prior to version 2.1.0 Service Pack 1"
}
]
}
}
]
},
"vendor_name": "Juniper Networks"
}
]
}
},
"data_format": "MITRE",
"data_type": "CVE",
"data_version": "4.0",
"description": {
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"value": "A denial of service vulnerability in Juniper Networks NorthStar Controller Application prior to version 2.1.0 Service Pack 1 may allow an unauthenticated, local user, to create a fork bomb scenario, also known as a rabbit virus, or wabbit, which will create processes that replicate themselves, until all resources are consumed on the system, leading to a denial of service to the entire system until it is restarted. Continued attacks by an unauthenticated, local user, can lead to persistent denials of services."
}
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"problemtype_data": [
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"value": "denial of service"
}
]
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},
"references": {
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"name": "https://kb.juniper.net/JSA10783",
"refsource": "CONFIRM",
"url": "https://kb.juniper.net/JSA10783"
},
{
"name": "97618",
"refsource": "BID",
"url": "http://www.securityfocus.com/bid/97618"
}
]
}
},
"nvd.nist.gov": {
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"versionEndIncluding": "2.1.0",
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"description": {
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}
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"value": "CWE-834"
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"impact": {
"baseMetricV2": {
"cvssV2": {
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"accessVector": "LOCAL",
"authentication": "NONE",
"availabilityImpact": "COMPLETE",
"baseScore": 4.9,
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:C",
"version": "2.0"
},
"exploitabilityScore": 3.9,
"impactScore": 6.9,
"obtainAllPrivilege": false,
"obtainOtherPrivilege": false,
"obtainUserPrivilege": false,
"severity": "MEDIUM",
"userInteractionRequired": false
},
"baseMetricV3": {
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"attackComplexity": "LOW",
"attackVector": "LOCAL",
"availabilityImpact": "HIGH",
"baseScore": 6.2,
"baseSeverity": "MEDIUM",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"version": "3.0"
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"exploitabilityScore": 2.5,
"impactScore": 3.6
}
},
"lastModifiedDate": "2019-10-03T00:03Z",
"publishedDate": "2017-04-24T15:59Z"
}
}
}
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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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