GSD-2018-0150
Vulnerability from gsd - Updated: 2023-12-13 01:22Details
A vulnerability in Cisco IOS XE Software could allow an unauthenticated, remote attacker to log in to a device running an affected release of Cisco IOS XE Software with the default username and password that are used at initial boot, aka a Static Credential Vulnerability. The vulnerability is due to an undocumented user account with privilege level 15 that has a default username and password. An attacker could exploit this vulnerability by using this account to remotely connect to an affected device. A successful exploit could allow the attacker to log in to the device with privilege level 15 access. This vulnerability affects Cisco devices that are running a vulnerable release of Cisco IOS XE Software Release 16.x. This vulnerability does not affect Cisco IOS XE Software releases prior to Release 16.x. Cisco Bug IDs: CSCve89880.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2018-0150",
"description": "A vulnerability in Cisco IOS XE Software could allow an unauthenticated, remote attacker to log in to a device running an affected release of Cisco IOS XE Software with the default username and password that are used at initial boot, aka a Static Credential Vulnerability. The vulnerability is due to an undocumented user account with privilege level 15 that has a default username and password. An attacker could exploit this vulnerability by using this account to remotely connect to an affected device. A successful exploit could allow the attacker to log in to the device with privilege level 15 access. This vulnerability affects Cisco devices that are running a vulnerable release of Cisco IOS XE Software Release 16.x. This vulnerability does not affect Cisco IOS XE Software releases prior to Release 16.x. Cisco Bug IDs: CSCve89880.",
"id": "GSD-2018-0150"
},
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"id": "GSD-2018-0150",
"modified": "2023-12-13T01:22:24.955890Z",
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}
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"baseScore": 10.0,
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"vectorString": "AV:N/AC:L/Au:N/C:C/I:C/A:C",
"version": "2.0"
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"severity": "HIGH",
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"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": "2023-05-22T17:08Z",
"publishedDate": "2018-03-28T22:29Z"
}
}
}
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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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