CVE-2013-7313 (GCVE-0-2013-7313)
Vulnerability from cvelistv5 – Published: 2014-01-23 17:00 – Updated: 2024-09-16 17:24
VLAI
EPSS
VEX
Summary
The OSPF implementation in Juniper Junos through 13.x, JunosE, and ScreenOS through 6.3.x does not consider the possibility of duplicate Link State ID values in Link State Advertisement (LSA) packets before performing operations on the LSA database, which allows remote attackers to cause a denial of service (routing disruption) or obtain sensitive packet information via a crafted LSA packet, a related issue to CVE-2013-0149.
Severity
No CVSS data available.
CWE
- n/a
Assigner
References
2 references
| URL | Tags |
|---|---|
| http://www.kb.cert.org/vuls/id/BLUU-97KQ26 | x_refsource_CONFIRM |
| http://www.kb.cert.org/vuls/id/229804 | third-party-advisoryx_refsource_CERT-VN |
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"lastModified": "2024-11-21T02:00:43.257",
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"value": "The OSPF implementation in Juniper Junos through 13.x, JunosE, and ScreenOS through 6.3.x does not consider the possibility of duplicate Link State ID values in Link State Advertisement (LSA) packets before performing operations on the LSA database, which allows remote attackers to cause a denial of service (routing disruption) or obtain sensitive packet information via a crafted LSA packet, a related issue to CVE-2013-0149."
},
{
"lang": "es",
"value": "La implementaci\u00f3n de OSPF en Juniper Junos hasta la versi\u00f3n 13.x, JunosE, y ScreenOS hasta la versi\u00f3n 6.3.x no considera la posibilidad de valores Link State ID duplicados en Link State Adverisement (LSA) antes de realizar operaciones en la base de datos LSA, lo que permite a atacantes remotos provocar una denegaci\u00f3n de servicio (interrupci\u00f3n de enrutamiento) u obtener informaci\u00f3n sensible de paquetes a trav\u00e9s de un paquete LSA manipulado, una vulnerabilidad relacionada con CVE-2013-0149."
}
],
"evaluatorComment": "Per: http://cwe.mitre.org/data/definitions/694.html\n\n\"CWE-694: Use of Multiple Resources with Duplicate Identifier\"",
"id": "CVE-2013-7313",
"lastModified": "2026-04-29T01:13:23.040",
"metrics": {
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}
}
}
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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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