GSD-2022-24044
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
A vulnerability has been identified in Desigo DXR2 (All versions < V01.21.142.5-22), Desigo PXC3 (All versions < V01.21.142.4-18), Desigo PXC4 (All versions < V02.20.142.10-10884), Desigo PXC5 (All versions < V02.20.142.10-10884). The login functionality of the application does not employ any countermeasures against Password Spraying attacks or Credential Stuffing attacks. An attacker could obtain a list of valid usernames on the device by exploiting the issue and then perform a precise Password Spraying or Credential Stuffing attack in order to obtain access to at least one account.
Aliases
Aliases
{
"GSD": {
"alias": "CVE-2022-24044",
"description": "A vulnerability has been identified in Desigo DXR2 (All versions \u003c V01.21.142.5-22), Desigo PXC3 (All versions \u003c V01.21.142.4-18), Desigo PXC4 (All versions \u003c V02.20.142.10-10884), Desigo PXC5 (All versions \u003c V02.20.142.10-10884). The login functionality of the application does not employ any countermeasures against Password Spraying attacks or Credential Stuffing attacks. An attacker could obtain a list of valid usernames on the device by exploiting the issue and then perform a precise Password Spraying or Credential Stuffing attack in order to obtain access to at least one account.",
"id": "GSD-2022-24044"
},
"gsd": {
"metadata": {
"exploitCode": "unknown",
"remediation": "unknown",
"reportConfidence": "confirmed",
"type": "vulnerability"
},
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"id": "GSD-2022-24044",
"modified": "2023-12-13T01:19:42.998544Z",
"schema_version": "1.4.0"
}
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}
]
},
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"name": "https://cert-portal.siemens.com/productcert/pdf/ssa-626968.pdf",
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"impact": {
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"cvssV2": {
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"accessVector": "NETWORK",
"authentication": "NONE",
"availabilityImpact": "NONE",
"baseScore": 5.0,
"confidentialityImpact": "PARTIAL",
"integrityImpact": "NONE",
"vectorString": "AV:N/AC:L/Au:N/C:P/I:N/A:N",
"version": "2.0"
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"confidentialityImpact": "HIGH",
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"scope": "UNCHANGED",
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"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
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},
"lastModifiedDate": "2022-06-01T15:28Z",
"publishedDate": "2022-05-20T13:15Z"
}
}
}
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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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